Safety logic for surgical suturing systems

ABSTRACT

A surgical suturing tracking system is disclosed. The surgical suturing tracking system is configured to detect and guide a suturing needle during a surgical suturing procedure. The surgical suturing track system comprises a control circuit configured to predict a path of a needle suturing stroke after receiving an input from a clinician, detect an embedded tissue structure, and assess proximity of the predicted path and the detected embedded tissue structure.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application claiming priority under 35U.S.C. § 121 to U.S. patent application Ser. No. 16/128,183, entitledSAFETY LOGIC FOR SURGICAL SUTURING SYSTEM, filed Sep. 11, 2018, now U.S.Patent Application Publication No. 2020/0015901, which claims thebenefit of priority under 35 U.S.C. § 119(e) to U.S. Provisional PatentApplication Ser. No. 62/698,625, titled DIGITAL SURGERYIMAGING/VISUALIZATION SYSTEM, filed Jul. 16, 2018, the disclosure ofwhich is herein incorporated by reference in its entirety.

BACKGROUND

Surgical systems often incorporate an imaging system, which can allowthe clinician(s) to view the surgical site and/or one or more portionsthereof on one or more displays such as a monitor, for example. Thedisplay(s) can be local and/or remote to a surgical theater. An imagingsystem can include a scope with a camera that views the surgical siteand transmits the view to a display that is viewable by a clinician.Scopes include, but are not limited to, arthroscopes, angioscopes,bronchoscopes, choledochoscopes, colonoscopes, cytoscopes,duodenoscopes, enteroscopes, esophagogastro-duodenoscopes(gastroscopes), endoscopes, laryngoscopes, nasopharyngo-neproscopes,sigmoidoscopes, thoracoscopes, ureteroscopes, and exoscopes. Imagingsystems can be limited by the information that they are able torecognize and/or convey to the clinician(s). For example, certainconcealed structures, physical contours, and/or dimensions within athree-dimensional space may be unrecognizable intraoperatively bycertain imaging systems. Additionally, certain imaging systems may beincapable of communicating and/or conveying certain information to theclinician(s) intraoperatively.

SUMMARY

In various embodiments, a surgical suturing tracking system configuredto detect and guide a suturing needle during a surgical suturingprocedure is disclosed. The surgical suturing tracking system comprisesa control circuit configured to predict a path of a needle suturingstroke after receiving an input from a clinician, detect an embeddedtissue structure, and assess proximity of the predicted path and thedetected embedded tissue structure.

FIGURES

The novel features of the various aspects are set forth withparticularity in the appended claims. The described aspects, however,both as to organization and methods of operation, may be best understoodby reference to the following description, taken in conjunction with theaccompanying drawings in which:

FIG. 1 is a schematic of a surgical visualization system including animaging device and a surgical device, the surgical visualization systemconfigured to identify a critical structure below a tissue surface,according to at least one aspect of the present disclosure.

FIG. 2 is a schematic of a control system for a surgical visualizationsystem, according to at least one aspect of the present disclosure.

FIG. 2A illustrates a control circuit configured to control aspects of asurgical visualization system, according to at least one aspect of thepresent disclosure.

FIG. 2B illustrates a combinational logic circuit configured to controlaspects of a surgical visualization system, according to at least oneaspect of the present disclosure.

FIG. 2C illustrates a sequential logic circuit configured to controlaspects of a surgical visualization system, according to at least oneaspect of the present disclosure.

FIG. 3 is a schematic depicting triangularization between the surgicaldevice, the imaging device, and the critical structure of FIG. 1 todetermine a depth d_(A) of the critical structure below the tissuesurface, according to at least one aspect of the present disclosure.

FIG. 4 is a schematic of a surgical visualization system configured toidentify a critical structure below a tissue surface, wherein thesurgical visualization system includes a pulsed light source fordetermining a depth d_(A) of the critical structure below the tissuesurface, according to at least one aspect of the present disclosure.

FIG. 5 is a schematic of a surgical visualization system including animaging device and a surgical device, the surgical visualization systemconfigured to identify a critical structure below a tissue surface,according to at least one aspect of the present disclosure.

FIG. 6 is a schematic of a surgical visualization system including athree-dimensional camera, wherein the surgical visualization system isconfigured to identify a critical structure that is embedded withintissue, according to at least one aspect of the present disclosure.

FIGS. 7A and 7B are views of the critical structure taken by thethree-dimensional camera of FIG. 6 , in which FIG. 7A is a view from aleft-side lens of the three-dimensional camera and FIG. 7B is a viewfrom a right-side lens of the three-dimensional camera, according to atleast one aspect of the present disclosure.

FIG. 8 is a schematic of the surgical visualization system of FIG. 6 ,in which a camera-to-critical structure distance d_(w) from thethree-dimensional camera to the critical structure can be determined,according to at least one aspect of the present disclosure.

FIG. 9 is a schematic of a surgical visualization system utilizing twocameras to determine the position of an embedded critical structure,according to at least one aspect of the present disclosure.

FIG. 10A is a schematic of a surgical visualization system utilizing acamera that is moved axially between a plurality of known positions todetermine a position of an embedded critical structure, according to atleast one aspect of the present disclosure.

FIG. 10B is a schematic of the surgical visualization system of FIG.10A, in which the camera is moved axially and rotationally between aplurality of known positions to determine a position of the embeddedcritical structure, according to at least one aspect of the presentdisclosure.

FIG. 11 is a schematic of a control system for a surgical visualizationsystem, according to at least one aspect of the present disclosure.

FIG. 12 is a schematic of a structured light source for a surgicalvisualization system, according to at least one aspect of the presentdisclosure.

FIG. 13 is a schematic of a hyperspectral visualization system forimaging terrestrial features or objects, according to at least oneaspect of the present disclosure.

FIG. 14 is a graphical representation of hyperspectral signatures forvarious terrestrial features or objects, according to at least oneaspect of the present disclosure.

FIGS. 15A-15C show an example of a hyperspectral visualization systemfor imaging a fried egg, wherein FIG. 15A is a photograph of the friedegg, FIG. 15B is a graphical representation of hyperspectral signaturesfor an egg yolk portion and an egg white portion of the fried egg, andFIG. 15C is a hyperspectral image (shown in black-and-white) of thefried egg, in which an augmented image differentiates between the eggyolk portion and the egg white portion based on hyperspectral signaturedata, according to at least one aspect of the present disclosure.

FIGS. 16-18 depict illustrative hyperspectral identifying signatures todifferentiate anatomy from obscurants, wherein FIG. 16 is a graphicalrepresentation of a ureter signature versus obscurants, FIG. 17 is agraphical representation of an artery signature versus obscurants, andFIG. 18 is a graphical representation of a nerve signature versusobscurants, according to at least one aspect of the present disclosure.

FIG. 19 is a schematic of a near infrared (NIR) time-of-flightmeasurement system configured to sense distance to a critical anatomicalstructure, the time-of-flight measurement system including a transmitter(emitter) and a receiver (sensor) positioned on a common device,according to at least one aspect of the present disclosure.

FIG. 20 is a schematic of an emitted wave, a received wave, and a delaybetween the emitted wave and the received wave of the NIR time-of-flightmeasurement system of FIG. 19 , according to at least one aspect of thepresent disclosure.

FIG. 21 illustrates a NIR time-of-flight measurement system configuredto sense a distance to different structures, the time-of-flightmeasurement system including a transmitter (emitter) and a receiver(sensor) on separate devices, according to one aspect of the presentdisclosure.

FIG. 22 is a partial perspective view of a robotically-assisted suturingsystem comprising a grasper, a suturing needle, and a surgicalvisualization assembly, according to at least one aspect of the presentdisclosure.

FIG. 23 is a perspective view a video monitor displaying informationgathered by a waveform sensor in a surgical site, according to at leastone aspect of the present disclosure.

FIG. 24 illustrates a first phase of a robotically assisted suturemotion using a grasper and a suture needle where a surgeon manuallytouches the suture needle to the surface of tissue with the grasper.

FIG. 25 illustrates a second phase of the robotically assisted suturemotion of FIG. 24 where a surgeon initiates an automatic,robotically-assisted portion of the suture motion where the grasper isactuated through a suturing stroke by the robotic system automatically.

FIG. 26 illustrates a third phase of the robotically assisted suturemotion of FIG. 24 where the grasper grabs a tip of the suture needle.

FIG. 27 is a flowchart depicting an algorithm for a surgicalvisualization feedback system used to determine the relative position ofa suturing needle and an embedded tissue structure.

FIG. 28 is a flowchart depicting an algorithm for a surgicalvisualization feedback system for use with a surgical suturing system.

FIG. 29 is a flowchart depicting an algorithm for a surgicalvisualization feedback system for use with a robotically-assistedsurgical suturing system.

FIG. 30 is a flowchart of a process utilizing a robotically assistedsuturing system, according to at least one aspect of the presentdisclosure.

FIG. 31 is a flowchart of a process utilizing a robotically assistedsuturing system, according to at least one aspect of the presentdisclosure.

DESCRIPTION

Applicant of the present application also owns the following U.S. patentapplications, filed on Sep. 11, 2018, each of which is hereinincorporated by reference in its entirety:

-   -   U.S. patent application Ser. No. 16/128,179, titled SURGICAL        VISUALIZATION PLATFORM, now U.S. Pat. No. 11,000,270;    -   U.S. patent application Ser. No. 16/128,191, titled SURGICAL        VISUALIZATION CONTROLS, now U.S. Patent Application Publication        No. 2020/0015904;    -   U.S. patent application Ser. No. 16/128,180, titled CONTROLLING        AN EMITTER ASSEMBLY PULSE SEQUENCE, now U.S. Patent Application        Publication No. 2020/0015900;    -   U.S. patent application Ser. No. 16/128,198, titled COMBINATION        EMITTER AND CAMERA ASSEMBLY, now U.S. Pat. No. 11,304,692;    -   U.S. patent application Ser. No. 16/128,207, titled SINGULAR EMR        SOURCE WITH DUAL OUTPUT EMITTER ASSEMBLY, now U.S. Patent        Application Publication No. 2020/0015925;    -   U.S. patent application Ser. No. 16/128,176, titled SURGICAL        VISUALIZATION WITH PROXIMITY TRACKING FEATURES, now U.S. Patent        Application Publication No. 2020/0015899;    -   U.S. patent application Ser. No. 16/128,187, titled SURGICAL        VISUALIZATION OF MULTIPLE TARGETS, now U.S. Patent Application        Publication No. 2020/0015899;    -   U.S. patent application Ser. No. 16/128,192, titled        VISUALIZATION OF SURGICAL DEVICES, now U.S. Pat. No. 10,792,034;    -   U.S. patent application Ser. No. 16/128,163, titled OPERATIVE        COMMUNICATION OF LIGHT, now U.S. Pat. No. 11,259,793;    -   U.S. patent application Ser. No. 16/128,197, titled ROBOTIC        LIGHT PROJECTION TOOLS, now U.S. Patent Application Publication        No. 2020/0015924;    -   U.S. patent application Ser. No. 16/128,164, titled SURGICAL        VISUALIZATION FEEDBACK SYSTEM, now U.S. Patent Application        Publication No. 2020/0015898;    -   U.S. patent application Ser. No. 16/128,193, titled SURGICAL        VISUALIZATION AND MONITORING, now U.S. Pat. No. 11,369,366    -   U.S. patent application Ser. No. 16/128,195, titled INTEGRATION        OF IMAGING DATA, now U.S. Patent Application Publication No.        2020/0015907;    -   U.S. patent application Ser. No. 16/128,170, titled        ROBOTICALLY-ASSISTED SURGICAL SUTURING SYSTEMS, now U.S. Pat.        No. 10,925,598;    -   U.S. patent application Ser. No. 16/128,172, titled ROBOTIC        SYSTEM WITH SEPARATE PHOTOACOUSTIC RECEIVER, now U.S. Patent        Application Publication No. 2020/0015914; and    -   U.S. patent application Ser. No. 16/128,185, titled FORCE SENSOR        THROUGH STRUCTURED LIGHT DEFLECTION, now U.S. Patent Application        Publication No. 2020/0015902.

Applicant of the present application also owns U.S. Pat. No. 9,072,535,titled SURGICAL STAPLING INSTRUMENTS WITH ROTATABLE STAPLE DEPLOYMENTARRANGEMENTS, issued Jul. 7, 2015, which is incorporated by referenceherein in its entirety.

Applicant of the present application also owns U.S. Provisional PatentApplication No. 62/611,339, titled ROBOT ASSISTED SURGICAL PLATFORM,filed Dec. 28, 2017, which is incorporated by reference herein in itsentirety.

Applicant of the present application also owns the following U.S. patentapplications, filed on Mar. 29, 2018, each of which is hereinincorporated by reference in its entirety:

-   -   U.S. patent application Ser. No. 15/940,627, titled DRIVE        ARRANGEMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS;    -   U.S. patent application Ser. No. 15/940,676, titled AUTOMATIC        TOOL ADJUSTMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS;    -   U.S. patent application Ser. No. 15/940,711, titled SENSING        ARRANGEMENTS FOR ROBOT-ASSISTED SURGICAL PLATFORMS; and    -   U.S. patent application Ser. No. 15/940,722, titled        CHARACTERIZATION OF TISSUE IRREGULARITIES THROUGH THE USE OF        MONO-CHROMATIC LIGHT REFRACTIVITY, filed Mar. 29, 2018, which is        incorporated by reference herein in its entirety.

Before explaining various aspects of a surgical visualization platformin detail, it should be noted that the illustrative examples are notlimited in application or use to the details of construction andarrangement of parts illustrated in the accompanying drawings anddescription. The illustrative examples may be implemented orincorporated in other aspects, variations, and modifications, and may bepracticed or carried out in various ways. Further, unless otherwiseindicated, the terms and expressions employed herein have been chosenfor the purpose of describing the illustrative examples for theconvenience of the reader and are not for the purpose of limitationthereof. Also, it will be appreciated that one or more of thefollowing-described aspects, expressions of aspects, and/or examples,can be combined with any one or more of the other following-describedaspects, expressions of aspects, and/or examples.

The present disclosure is directed to a surgical visualization platformthat leverages “digital surgery” to obtain additional information abouta patient's anatomy and/or a surgical procedure. The surgicalvisualization platform is further configured to convey data and/orinformation to one or more clinicians in a helpful manner. For example,various aspects of the present disclosure provide improved visualizationof the patient's anatomy and/or the surgical procedure.

“Digital surgery” can embrace robotic systems, advanced imaging,advanced instrumentation, artificial intelligence, machine learning,data analytics for performance tracking and benchmarking, connectivityboth inside and outside of the operating room (OR), and more. Althoughvarious surgical visualization platforms described herein can be used incombination with a robotic surgical system, surgical visualizationplatforms are not limited to use with a robotic surgical system. Incertain instances, advanced surgical visualization can occur withoutrobotics and/or with limited and/or optional robotic assistance.Similarly, digital surgery can occur without robotics and/or withlimited and/or optional robotic assistance.

In certain instances, a surgical system that incorporates a surgicalvisualization platform may enable smart dissection in order to identifyand avoid critical structures. Critical structures include anatomicalstructures such as a ureter, an artery such as a superior mesentericartery, a vein such as a portal vein, a nerve such as a phrenic nerve,and/or a tumor, among other anatomical structures. In other instances, acritical structure can be a foreign structure in the anatomical field,such as a surgical device, surgical fastener, clip, tack, bougie, band,and/or plate, for example. Critical structures can be determined on apatient-by-patient and/or a procedure-by-procedure basis. Examplecritical structures are further described herein. Smart dissectiontechnology may provide improved intraoperative guidance for dissectionand/or can enable smarter decisions with critical anatomy detection andavoidance technology, for example.

A surgical system incorporating a surgical visualization platform mayalso enable smart anastomosis technologies that provide more consistentanastomoses at optimal location(s) with improved workflow. Cancerlocalization technologies may also be improved with the various surgicalvisualization platforms and procedures described herein. For example,cancer localization technologies can identify and track a cancerlocation, orientation, and its margins. In certain instances, the cancerlocalizations technologies may compensate for movement of a tool, apatient, and/or the patient's anatomy during a surgical procedure inorder to provide guidance back to the point of interest for theclinician.

In certain aspects of the present disclosure, a surgical visualizationplatform may provide improved tissue characterization and/or lymph nodediagnostics and mapping. For example, tissue characterizationtechnologies may characterize tissue type and health without the needfor physical haptics, especially when dissecting and/or placing staplingdevices within the tissue. Certain tissue characterization technologiesdescribed herein may be utilized without ionizing radiation and/orcontrast agents. With respect to lymph node diagnostics and mapping, asurgical visualization platform may preoperatively locate, map, andideally diagnose the lymph system and/or lymph nodes involved incancerous diagnosis and staging, for example.

These and other related topics are described herein and/or in theaforementioned contemporaneously-filed U.S. patent applications, whichare incorporated by reference herein in their respective entireties.

During a surgical procedure, the information available to the clinicianvia the “naked eye” and/or an imaging system may provide an incompleteview of the surgical site. For example, certain structures, such asstructures embedded or buried within an organ, can be at least partiallyconcealed or hidden from view. Additionally, certain dimensions and/orrelative distances can be difficult to ascertain with existing sensorsystems and/or difficult for the “naked eye” to perceive. Moreover,certain structures can move preoperatively (e.g. before a surgicalprocedure but after a preoperative scan) and/or intraoperatively. Insuch instances, the clinician can be unable to accurately determine thelocation of a critical structure intraoperatively.

When the position of a critical structure is uncertain and/or when theproximity between the critical structure and a surgical tool is unknown,a clinician's decision-making process can be inhibited. For example, aclinician may avoid certain areas in order to avoid inadvertentdissection of a critical structure; however, the avoided area may beunnecessarily large and/or at least partially misplaced. Due touncertainty and/or overly/excessive exercises in caution, the clinicianmay not access certain desired regions. For example, excess caution maycause a clinician to leave a portion of a tumor and/or other undesirabletissue in an effort to avoid a critical structure even if the criticalstructure is not in the particular area and/or would not be negativelyimpacted by the clinician working in that particular area. In certaininstances, surgical results can be improved with increased knowledgeand/or certainty, which can allow a surgeon to be more accurate and, incertain instances, less conservative/more aggressive with respect toparticular anatomical areas.

In various aspects, the present disclosure provides a surgicalvisualization system for intraoperative identification and avoidance ofcritical structures. In one aspect, the present disclosure provides asurgical visualization system that enables enhanced intraoperativedecision making and improved surgical outcomes. In various aspects, thedisclosed surgical visualization system provides advanced visualizationcapabilities beyond what a clinician sees with the “naked eye” and/orbeyond what an imaging system can recognize and/or convey to theclinician. The various surgical visualization systems can augment andenhance what a clinician is able to know prior to tissue treatment (e.g.dissection) and, thus, may improve outcomes in various instances.

For example, a visualization system can include a first light emitterconfigured to emit a plurality of spectral waves, a second light emitterconfigured to emit a light pattern, and one or more receivers, orsensors, configured to detect visible light, molecular responses to thespectral waves (spectral imaging), and/or the light pattern. Thesurgical visualization system can also include an imaging system and acontrol circuit in signal communication with the receiver(s) and theimaging system. Based on output from the receiver(s), the controlcircuit can determine a geometric surface map, i.e. three-dimensionalsurface topography, of the visible surfaces at the surgical site and oneor more distances with respect to the surgical site. In certaininstances, the control circuit can determine one more distances to an atleast partially concealed structure. Moreover, the imaging system canconvey the geometric surface map and the one or more distances to aclinician. In such instances, an augmented view of the surgical siteprovided to the clinician can provide a representation of the concealedstructure within the relevant context of the surgical site. For example,the imaging system can virtually augment the concealed structure on thegeometric surface map of the concealing and/or obstructing tissuesimilar to a line drawn on the ground to indicate a utility line belowthe surface. Additionally or alternatively, the imaging system canconvey the proximity of one or more surgical tools to the visible andobstructing tissue and/or to the at least partially concealed structureand/or the depth of the concealed structure below the visible surface ofthe obstructing tissue. For example, the visualization system candetermine a distance with respect to the augmented line on the surfaceof the visible tissue and convey the distance to the imaging system.

In various aspects of the present disclosure, a surgical visualizationsystem is disclosed for intraoperative identification and avoidance ofcritical structures. Such a surgical visualization system can providevaluable information to a clinician during a surgical procedure. As aresult, the clinician can confidently maintain momentum throughout thesurgical procedure knowing that the surgical visualization system istracking a critical structure such as a ureter, specific nerves, and/orcritical blood vessels, for example, which may be approached duringdissection, for example. In one aspect, the surgical visualizationsystem can provide an indication to the clinician in sufficient time forthe clinician to pause and/or slow down the surgical procedure andevaluate the proximity to the critical structure to prevent inadvertentdamage thereto. The surgical visualization system can provide an ideal,optimized, and/or customizable amount of information to the clinician toallow the clinician to move confidently and/or quickly through tissuewhile avoiding inadvertent damage to healthy tissue and/or criticalstructure(s) and, thus, to minimize the risk of harm resulting from thesurgical procedure.

FIG. 1 is a schematic of a surgical visualization system 100 accordingto at least one aspect of the present disclosure. The surgicalvisualization system 100 can create a visual representation of acritical structure 101 within an anatomical field. The surgicalvisualization system 100 can be used for clinical analysis and/ormedical intervention, for example. In certain instances, the surgicalvisualization system 100 can be used intraoperatively to providereal-time, or near real-time, information to the clinician regardingproximity data, dimensions, and/or distances during a surgicalprocedure. The surgical visualization system 100 is configured forintraoperative identification of critical structure(s) and/or tofacilitate the avoidance of the critical structure(s) 101 by a surgicaldevice. For example, by identifying the critical structure 101, aclinician can avoid maneuvering a surgical device around the criticalstructure 101 and/or a region in a predefined proximity of the criticalstructure 101 during a surgical procedure. The clinician can avoiddissection of and/or near a vein, artery, nerve, and/or vessel, forexample, identified as the critical structure 101, for example. Invarious instances, the critical structure 101 can be determined on apatient-by-patient and/or a procedure-by-procedure basis.

The surgical visualization system 100 incorporates tissue identificationand geometric surface mapping in combination with a distance sensorsystem 104. In combination, these features of the surgical visualizationsystem 100 can determine a position of a critical structure 101 withinthe anatomical field and/or the proximity of a surgical device 102 tothe surface 105 of the visible tissue and/or to the critical structure101. Moreover, the surgical visualization system 100 includes an imagingsystem that includes an imaging device 120, such as a camera, forexample, configured to provide real-time views of the surgical site. Invarious instances, the imaging device 120 is a spectral camera (e.g. ahyperspectral camera, multispectral camera, or selective spectralcamera), which is configured to detect reflected spectral waveforms andgenerate a spectral cube of images based on the molecular response tothe different wavelengths. Views from the imaging device 120 can beprovided to a clinician and, in various aspects of the presentdisclosure, can be augmented with additional information based on thetissue identification, landscape mapping, and the distance sensor system104. In such instances, the surgical visualization system 100 includes aplurality of subsystems—an imaging subsystem, a surface mappingsubsystem, a tissue identification subsystem, and/or a distancedetermining subsystem. These subsystems can cooperate tointraoperatively provide advanced data synthesis and integratedinformation to the clinician(s).

The imaging device can include a camera or imaging sensor that isconfigured to detect visible light, spectral light waves (visible orinvisible), and a structured light pattern (visible or invisible), forexample. In various aspects of the present disclosure, the imagingsystem can include an imaging device such as an endoscope, for example.Additionally or alternatively, the imaging system can include an imagingdevice such as an arthroscope, angioscope, bronchoscope,choledochoscope, colonoscope, cytoscope, duodenoscope, enteroscope,esophagogastro-duodenoscope (gastroscope), laryngoscope,nasopharyngo-neproscope, sigmoidoscope, thoracoscope, ureteroscope, orexoscope, for example. In other instances, such as in open surgeryapplications, the imaging system may not include a scope.

In various aspects of the present disclosure, the tissue identificationsubsystem can be achieved with a spectral imaging system. The spectralimaging system can rely on hyperspectral imaging, multispectral imaging,or selective spectral imaging, for example. Hyperspectral imaging oftissue is further described in U.S. Pat. No. 9,274,047, titled SYSTEMAND METHOD FOR GROSS ANATOMIC PATHOLOGY USING HYPERSPECTRAL IMAGING,issued Mar. 1, 2016, which is incorporated by reference herein in itsentirety.

In various aspect of the present disclosure, the surface mappingsubsystem can be achieved with a light pattern system, as furtherdescribed herein. The use of a light pattern (or structured light) forsurface mapping is known. Known surface mapping techniques can beutilized in the surgical visualization systems described herein.

Structured light is the process of projecting a known pattern (often agrid or horizontal bars) on to a surface. U.S. Patent ApplicationPublication No. 2017/0055819, titled SET COMPRISING A SURGICALINSTRUMENT, published Mar. 2, 2017, and U.S. Patent ApplicationPublication No. 2017/0251900, titled DEPICTION SYSTEM, published Sep. 7,2017, disclose a surgical system comprising a light source and aprojector for projecting a light pattern. U.S. Patent ApplicationPublication No. 2017/0055819, titled SET COMPRISING A SURGICALINSTRUMENT, published Mar. 2, 2017, and U.S. Patent ApplicationPublication No. 2017/0251900, titled DEPICTION SYSTEM, published Sep. 7,2017, are incorporated by reference herein in their respectiveentireties.

In various aspects of the present disclosure, the distance determiningsystem can be incorporated into the surface mapping system. For example,structured light can be utilized to generate a three-dimensional virtualmodel of the visible surface and determine various distances withrespect to the visible surface. Additionally or alternatively, thedistance determining system can rely on time-of-flight measurements todetermine one or more distances to the identified tissue (or otherstructures) at the surgical site.

FIG. 2 is a schematic diagram of a control system 133, which can beutilized with the surgical visualization system 100. The control system133 includes a control circuit 132 in signal communication with a memory134. The memory 134 stores instructions executable by the controlcircuit 132 to determine and/or recognize critical structures (e.g. thecritical structure 101 in FIG. 1 ), determine and/or compute one or moredistances and/or three-dimensional digital representations, and tocommunicate certain information to one or more clinicians. For example,the memory 134 stores surface mapping logic 136, imaging logic 138,tissue identification logic 140, or distance determining logic 141 orany combinations of the logic 136, 138, 140, and 141. The control system133 also includes an imaging system 142 having one or more cameras 144(like the imaging device 120 in FIG. 1 ), one or more displays 146, orone or more controls 148 or any combinations of these elements. Thecamera 144 can include one or more image sensors 135 to receive signalsfrom various light sources emitting light at various visible andinvisible spectra (e.g. visible light, spectral imagers,three-dimensional lens, among others). The display 146 can include oneor more screens or monitors for depicting real, virtual, and/orvirtually-augmented images and/or information to one or more clinicians.

In various aspects, the heart of the camera 144 is the image sensor 135.Generally, modern image sensors 135 are solid-state electronic devicescontaining up to millions of discrete photodetector sites called pixels.The image sensor 135 technology falls into one of two categories:Charge-Coupled Device (CCD) and Complementary Metal Oxide Semiconductor(CMOS) imagers and more recently, short-wave infrared (SWIR) is anemerging technology in imaging. Another type of image sensor 135 employsa hybrid CCD/CMOS architecture (sold under the name “sCMOS”) andconsists of CMOS readout integrated circuits (ROICs) that are bumpbonded to a CCD imaging substrate. CCD and CMOS image sensors 135 aresensitive to wavelengths from approximately 350-1050 nm, although therange is usually given from 400-1000 nm. CMOS sensors are, in general,more sensitive to IR wavelengths than CCD sensors. Solid state imagesensors 135 are based on the photoelectric effect and, as a result,cannot distinguish between colors. Accordingly, there are two types ofcolor CCD cameras: single chip and three-chip. Single chip color CCDcameras offer a common, low-cost imaging solution and use a mosaic (e.g.Bayer) optical filter to separate incoming light into a series of colorsand employ an interpolation algorithm to resolve full color images. Eachcolor is, then, directed to a different set of pixels. Three-chip colorCCD cameras provide higher resolution by employing a prism to directeach section of the incident spectrum to a different chip. More accuratecolor reproduction is possible, as each point in space of the object hasseparate RGB intensity values, rather than using an algorithm todetermine the color. Three-chip cameras offer extremely highresolutions.

The control system 133 also includes a spectral light source 150 and astructured light source 152. In certain instances, a single source canbe pulsed to emit wavelengths of light in the spectral light source 150range and wavelengths of light in the structured light source 152 range.Alternatively, a single light source can be pulsed to provide light inthe invisible spectrum (e.g. infrared spectral light) and wavelengths oflight on the visible spectrum. The spectral light source 150 can be ahyperspectral light source, a multispectral light source, and/or aselective spectral light source, for example. In various instances, thetissue identification logic 140 can identify critical structure(s) viadata from the spectral light source 150 received by the image sensor 135portion of the camera 144. The surface mapping logic 136 can determinethe surface contours of the visible tissue based on reflected structuredlight. With time-of-flight measurements, the distance determining logic141 can determine one or more distance(s) to the visible tissue and/orthe critical structure 101. One or more outputs from the surface mappinglogic 136, the tissue identification logic 140, and the distancedetermining logic 141, can be provided to the imaging logic 138, andcombined, blended, and/or overlaid to be conveyed to a clinician via thedisplay 146 of the imaging system 142.

The description now turns briefly to FIGS. 2A-2C to describe variousaspects of the control circuit 132 for controlling various aspects ofthe surgical visualization system 100. Turning to FIG. 2A, there isillustrated a control circuit 400 configured to control aspects of thesurgical visualization system 100, according to at least one aspect ofthis disclosure. The control circuit 400 can be configured to implementvarious processes described herein. The control circuit 400 may comprisea microcontroller comprising one or more processors 402 (e.g.,microprocessor, microcontroller) coupled to at least one memory circuit404. The memory circuit 404 stores machine-executable instructions that,when executed by the processor 402, cause the processor 402 to executemachine instructions to implement various processes described herein.The processor 402 may be any one of a number of single-core or multicoreprocessors known in the art. The memory circuit 404 may comprisevolatile and non-volatile storage media. The processor 402 may includean instruction processing unit 406 and an arithmetic unit 408. Theinstruction processing unit may be configured to receive instructionsfrom the memory circuit 404 of this disclosure.

FIG. 2B illustrates a combinational logic circuit 410 configured tocontrol aspects of the surgical visualization system 100, according toat least one aspect of this disclosure. The combinational logic circuit410 can be configured to implement various processes described herein.The combinational logic circuit 410 may comprise a finite state machinecomprising a combinational logic 412 configured to receive dataassociated with the surgical instrument or tool at an input 414, processthe data by the combinational logic 412, and provide an output 416.

FIG. 2C illustrates a sequential logic circuit 420 configured to controlaspects of the surgical visualization system 100, according to at leastone aspect of this disclosure. The sequential logic circuit 420 or thecombinational logic 422 can be configured to implement various processesdescribed herein. The sequential logic circuit 420 may comprise a finitestate machine. The sequential logic circuit 420 may comprise acombinational logic 422, at least one memory circuit 424, and a clock429, for example. The at least one memory circuit 424 can store acurrent state of the finite state machine. In certain instances, thesequential logic circuit 420 may be synchronous or asynchronous. Thecombinational logic 422 is configured to receive data associated with asurgical device or system from an input 426, process the data by thecombinational logic 422, and provide an output 428. In other aspects,the circuit may comprise a combination of a processor (e.g., processor402 in FIG. 2A) and a finite state machine to implement variousprocesses herein. In other aspects, the finite state machine maycomprise a combination of a combinational logic circuit (e.g.,combinational logic circuit 410, FIG. 2B) and the sequential logiccircuit 420.

Referring again to the surgical visualization system 100 in FIG. 1 , thecritical structure 101 can be an anatomical structure of interest. Forexample, the critical structure 101 can be a ureter, an artery such as asuperior mesenteric artery, a vein such as a portal vein, a nerve suchas a phrenic nerve, and/or a tumor, among other anatomical structures.In other instances, the critical structure 101 can be a foreignstructure in the anatomical field, such as a surgical device, surgicalfastener, clip, tack, bougie, band, and/or plate, for example. Examplecritical structures are further described herein and in theaforementioned contemporaneously-filed U.S. patent applications,including U.S. patent application Ser. No. 16/128,192, titledVISUALIZATION OF SURGICAL DEVICES, for example, which are incorporatedby reference herein in their respective entireties.

In one aspect, the critical structure 101 may be embedded in tissue 103.Stated differently, the critical structure 101 may be positioned belowthe surface 105 of the tissue 103. In such instances, the tissue 103conceals the critical structure 101 from the clinician's view. Thecritical structure 101 is also obscured from the view of the imagingdevice 120 by the tissue 103. The tissue 103 can be fat, connectivetissue, adhesions, and/or organs, for example. In other instances, thecritical structure 101 can be partially obscured from view.

FIG. 1 also depicts the surgical device 102. The surgical device 102includes an end effector having opposing jaws extending from the distalend of the shaft of the surgical device 102. The surgical device 102 canbe any suitable surgical device such as, for example, a dissector, astapler, a grasper, a clip applier, and/or an energy device includingmono-polar probes, bi-polar probes, ablation probes, and/or anultrasonic end effector. Additionally or alternatively, the surgicaldevice 102 can include another imaging or diagnostic modality, such asan ultrasound device, for example. In one aspect of the presentdisclosure, the surgical visualization system 100 can be configured toachieve identification of one or more critical structures 101 and theproximity of the surgical device 102 to the critical structure(s) 101.

The imaging device 120 of the surgical visualization system 100 isconfigured to detect light at various wavelengths, such as, for example,visible light, spectral light waves (visible or invisible), and astructured light pattern (visible or invisible). The imaging device 120may include a plurality of lenses, sensors, and/or receivers fordetecting the different signals. For example, the imaging device 120 canbe a hyperspectral, multispectral, or selective spectral camera, asfurther described herein. The imaging device 120 can also include awaveform sensor 122 (such as a spectral image sensor, detector, and/orthree-dimensional camera lens). For example, the imaging device 120 caninclude a right-side lens and a left-side lens used together to recordtwo two-dimensional images at the same time and, thus, generate athree-dimensional image of the surgical site, render a three-dimensionalimage of the surgical site, and/or determine one or more distances atthe surgical site. Additionally or alternatively, the imaging device 120can be configured to receive images indicative of the topography of thevisible tissue and the identification and position of hidden criticalstructures, as further described herein. For example, the field of viewof the imaging device 120 can overlap with a pattern of light(structured light) on the surface 105 of the tissue, as shown in FIG. 1.

In one aspect, the surgical visualization system 100 may be incorporatedinto a robotic system 110. For example, the robotic system 110 mayinclude a first robotic arm 112 and a second robotic arm 114. Therobotic arms 112, 114 include rigid structural members 116 and joints118, which can include servomotor controls. The first robotic arm 112 isconfigured to maneuver the surgical device 102, and the second roboticarm 114 is configured to maneuver the imaging device 120. A roboticcontrol unit can be configured to issue control motions to the roboticarms 112, 114, which can affect the surgical device 102 and the imagingdevice 120, for example.

The surgical visualization system 100 also includes an emitter 106,which is configured to emit a pattern of light, such as stripes, gridlines, and/or dots, to enable the determination of the topography orlandscape of the surface 105. For example, projected light arrays 130can be used for three-dimensional scanning and registration on thesurface 105. The projected light arrays 130 can be emitted from theemitter 106 located on the surgical device 102 and/or one of the roboticarms 112, 114 and/or the imaging device 120, for example. In one aspect,the projected light array 130 is employed to determine the shape definedby the surface 105 of the tissue 103 and/or the motion of the surface105 intraoperatively. The imaging device 120 is configured to detect theprojected light arrays 130 reflected from the surface 105 to determinethe topography of the surface 105 and various distances with respect tothe surface 105.

In one aspect, the imaging device 120 also may include an opticalwaveform emitter 123 that is configured to emit electromagneticradiation 124 (NIR photons) that can penetrate the surface 105 of thetissue 103 and reach the critical structure 101. The imaging device 120and the optical waveform emitter 123 thereon can be positionable by therobotic arm 114. A corresponding waveform sensor 122 (an image sensor,spectrometer, or vibrational sensor, for example) on the imaging device120 is configured to detect the effect of the electromagnetic radiationreceived by the waveform sensor 122. The wavelengths of theelectromagnetic radiation 124 emitted by the optical waveform emitter123 can be configured to enable the identification of the type ofanatomical and/or physical structure, such as the critical structure101. The identification of the critical structure 101 can beaccomplished through spectral analysis, photo-acoustics, and/orultrasound, for example. In one aspect, the wavelengths of theelectromagnetic radiation 124 may be variable. The waveform sensor 122and optical waveform emitter 123 may be inclusive of a multispectralimaging system and/or a selective spectral imaging system, for example.In other instances, the waveform sensor 122 and optical waveform emitter123 may be inclusive of a photoacoustic imaging system, for example. Inother instances, the optical waveform emitter 123 can be positioned on aseparate surgical device from the imaging device 120.

The surgical visualization system 100 also may include the distancesensor system 104 configured to determine one or more distances at thesurgical site. In one aspect, the time-of-flight distance sensor system104 may be a time-of-flight distance sensor system that includes anemitter, such as the emitter 106, and a receiver 108, which can bepositioned on the surgical device 102. In other instances, thetime-of-flight emitter can be separate from the structured lightemitter. In one general aspect, the emitter 106 portion of thetime-of-flight distance sensor system 104 may include a very tiny lasersource and the receiver 108 portion of the time-of-flight distancesensor system 104 may include a matching sensor. The time-of-flightdistance sensor system 104 can detect the “time of flight,” or how longthe laser light emitted by the emitter 106 has taken to bounce back tothe sensor portion of the receiver 108. Use of a very narrow lightsource in the emitter 106 enables the distance sensor system 104 todetermining the distance to the surface 105 of the tissue 103 directlyin front of the distance sensor system 104. Referring still to FIG. 1 ,d_(e) is the emitter-to-tissue distance from the emitter 106 to thesurface 105 of the tissue 103 and d_(t) is the device-to-tissue distancefrom the distal end of the surgical device 102 to the surface 105 of thetissue. The distance sensor system 104 can be employed to determine theemitter-to-tissue distance d_(e). The device-to-tissue distance d_(t) isobtainable from the known position of the emitter 106 on the shaft ofthe surgical device 102 relative to the distal end of the surgicaldevice 102. In other words, when the distance between the emitter 106and the distal end of the surgical device 102 is known, thedevice-to-tissue distance d_(t) can be determined from theemitter-to-tissue distance d_(e). In certain instances, the shaft of thesurgical device 102 can include one or more articulation joints, and canbe articulatable with respect to the emitter 106 and the jaws. Thearticulation configuration can include a multi-joint vertebrae-likestructure, for example. In certain instances, a three-dimensional cameracan be utilized to triangulate one or more distances to the surface 105.

In various instances, the receiver 108 for the time-of-flight distancesensor system 104 can be mounted on a separate surgical device insteadof the surgical device 102. For example, the receiver 108 can be mountedon a cannula or trocar through which the surgical device 102 extends toreach the surgical site. In still other instances, the receiver 108 forthe time-of-flight distance sensor system 104 can be mounted on aseparate robotically-controlled arm (e.g. the robotic arm 114), on amovable arm that is operated by another robot, and/or to an operatingroom (OR) table or fixture. In certain instances, the imaging device 120includes the time-of-flight receiver 108 to determine the distance fromthe emitter 106 to the surface 105 of the tissue 103 using a linebetween the emitter 106 on the surgical device 102 and the imagingdevice 120. For example, the distance d_(e) can be triangulated based onknown positions of the emitter 106 (on the surgical device 102) and thereceiver 108 (on the imaging device 120) of the time-of-flight distancesensor system 104. The three-dimensional position of the receiver 108can be known and/or registered to the robot coordinate planeintraoperatively.

In certain instances, the position of the emitter 106 of thetime-of-flight distance sensor system 104 can be controlled by the firstrobotic arm 112 and the position of the receiver 108 of thetime-of-flight distance sensor system 104 can be controlled by thesecond robotic arm 114. In other instances, the surgical visualizationsystem 100 can be utilized apart from a robotic system. In suchinstances, the distance sensor system 104 can be independent of therobotic system.

In certain instances, one or more of the robotic arms 112, 114 may beseparate from a main robotic system used in the surgical procedure. Atleast one of the robotic arms 112, 114 can be positioned and registeredto a particular coordinate system without a servomotor control. Forexample, a closed-loop control system and/or a plurality of sensors forthe robotic arms 110 can control and/or register the position of therobotic arm(s) 112, 114 relative to the particular coordinate system.Similarly, the position of the surgical device 102 and the imagingdevice 120 can be registered relative to a particular coordinate system.

Referring still to FIG. 1 , d_(w) is the camera-to-critical structuredistance from the optical waveform emitter 123 located on the imagingdevice 120 to the surface of the critical structure 101, and d_(A) isthe depth of the critical structure 101 below the surface 105 of thetissue 103 (i.e., the distance between the portion of the surface 105closest to the surgical device 102 and the critical structure 101). Invarious aspects, the time-of-flight of the optical waveforms emittedfrom the optical waveform emitter 123 located on the imaging device 120can be configured to determine the camera-to-critical structure distanced_(w). The use of spectral imaging in combination with time-of-flightsensors is further described herein. Moreover, referring now to FIG. 3 ,in various aspects of the present disclosure, the depth d_(A) of thecritical structure 101 relative to the surface 105 of the tissue 103 canbe determined by triangulating from the distance d_(w) and knownpositions of the emitter 106 on the surgical device 102 and the opticalwaveform emitter 123 on the imaging device 120 (and, thus, the knowndistance d_(x) therebetween) to determine the distance d_(y), which isthe sum of the distances d_(e) and d_(A).

Additionally or alternatively, time-of-flight from the optical waveformemitter 123 can be configured to determine the distance from the opticalwaveform emitter 123 to the surface 105 of the tissue 103. For example,a first waveform (or range of waveforms) can be utilized to determinethe camera-to-critical structure distance d_(w) and a second waveform(or range of waveforms) can be utilized to determine the distance to thesurface 105 of the tissue 103. In such instances, the differentwaveforms can be utilized to determine the depth of the criticalstructure 101 below the surface 105 of the tissue 103.

Additionally or alternatively, in certain instances, the distance d_(A)can be determined from an ultrasound, a registered magnetic resonanceimaging (MRI) or computerized tomography (CT) scan. In still otherinstances, the distance d_(A) can be determined with spectral imagingbecause the detection signal received by the imaging device can varybased on the type of material. For example, fat can decrease thedetection signal in a first way, or a first amount, and collagen candecrease the detection signal in a different, second way, or a secondamount.

Referring now to a surgical visualization system 160 in FIG. 4 , inwhich a surgical device 162 includes the optical waveform emitter 123and the waveform sensor 122 that is configured to detect the reflectedwaveforms. The optical waveform emitter 123 can be configured to emitwaveforms for determining the distances d_(t) and d_(w) from a commondevice, such as the surgical device 162, as further described herein. Insuch instances, the distance d_(A) from the surface 105 of the tissue103 to the surface of the critical structure 101 can be determined asfollows:

d _(A) =d _(w) −d _(t).

As disclosed herein, various information regarding visible tissue,embedded critical structures, and surgical devices can be determined byutilizing a combination approach that incorporates one or moretime-of-flight distance sensors, spectral imaging, and/or structuredlight arrays in combination with an image sensor configured to detectthe spectral wavelengths and the structured light arrays. Moreover, theimage sensor can be configured to receive visible light and, thus,provide images of the surgical site to an imaging system. Logic oralgorithms are employed to discern the information received from thetime-of-flight sensors, spectral wavelengths, structured light, andvisible light and render three-dimensional images of the surface tissueand underlying anatomical structures. In various instances, the imagingdevice 120 can include multiple image sensors.

The camera-to-critical structure distance d_(w) can also be detected inone or more alternative ways. In one aspect, a fluoroscopy visualizationtechnology, such as fluorescent indosciedine green (ICG), for example,can be utilized to illuminate a critical structure 201, as shown inFIGS. 6-8 . A camera 220 can include two optical waveforms sensors 222,224, which take simultaneous left-side and right-side images of thecritical structure 201 (FIGS. 7A and 7B). In such instances, the camera220 can depict a glow of the critical structure 201 below the surface205 of the tissue 203, and the distance d_(w) can be determined by theknown distance between the sensors 222 and 224. In certain instances,distances can be determined more accurately by utilizing more than onecamera or by moving a camera between multiple locations. In certainaspects, one camera can be controlled by a first robotic arm and asecond camera by another robotic arm. In such a robotic system, onecamera can be a follower camera on a follower arm, for example. Thefollower arm, and camera thereon, can be programmed to track the othercamera and to maintain a particular distance and/or lens angle, forexample.

In still other aspects, the surgical visualization system 100 may employtwo separate waveform receivers (i.e. cameras/image sensors) todetermine d_(w). Referring now to FIG. 9 , if a critical structure 301or the contents thereof (e.g. a vessel or the contents of the vessel)can emit a signal 302, such as with fluoroscopy, then the actuallocation can be triangulated from two separate cameras 320 a, 320 b atknown locations.

In another aspect, referring now to FIGS. 10A and 10B, a surgicalvisualization system may employ a dithering or moving camera 440 todetermine the distance d_(w). The camera 440 is robotically-controlledsuch that the three-dimensional coordinates of the camera 440 at thedifferent positions are known. In various instances, the camera 440 canpivot at a cannula or patient interface. For example, if a criticalstructure 401 or the contents thereof (e.g. a vessel or the contents ofthe vessel) can emit a signal, such as with fluoroscopy, for example,then the actual location can be triangulated from the camera 440 movedrapidly between two or more known locations. In FIG. 10A, the camera 440is moved axially along an axis A. More specifically, the camera 440translates a distance d₁ closer to the critical structure 401 along theaxis A to the location indicated as a location 440′, such as by movingin and out on a robotic arm. As the camera 440 moves the distance d₁ andthe size of view change with respect to the critical structure 401, thedistance to the critical structure 401 can be calculated. For example, a4.28 mm axial translation (the distance d₁) can correspond to an angleθ₁ of 6.28 degrees and an angle θ₂ of 8.19 degrees. Additionally oralternatively, the camera 440 can rotate or sweep along an arc betweendifferent positions. Referring now to FIG. 10B, the camera 440 is movedaxially along the axis A and is rotated an angle θ₃ about the axis A. Apivot point 442 for rotation of the camera 440 is positioned at thecannula/patient interface. In FIG. 10B, the camera 440 is translated androtated to a location 440″. As the camera 440 moves and the edge of viewchanges with respect to the critical structure 401, the distance to thecritical structure 401 can be calculated. In FIG. 10B, a distance d₂ canbe 9.01 mm, for example, and the angle θ₃ can be 0.9 degrees, forexample.

FIG. 5 depicts a surgical visualization system 500, which is similar tothe surgical visualization system 100 in many respects. In variousinstances, the surgical visualization system 500 can be a furtherexemplification of the surgical visualization system 100. Similar to thesurgical visualization system 100, the surgical visualization system 500includes a surgical device 502 and an imaging device 520. The imagingdevice 520 includes a spectral light emitter 523, which is configured toemit spectral light in a plurality of wavelengths to obtain a spectralimage of hidden structures, for example. The imaging device 520 can alsoinclude a three-dimensional camera and associated electronic processingcircuits in various instances. The surgical visualization system 500 isshown being utilized intraoperatively to identify and facilitateavoidance of certain critical structures, such as a ureter 501 a andvessels 501 b in an organ 503 (the uterus in this example), that are notvisible on the surface.

The surgical visualization system 500 is configured to determine anemitter-to-tissue distance d_(e) from an emitter 506 on the surgicaldevice 502 to a surface 505 of the uterus 503 via structured light. Thesurgical visualization system 500 is configured to extrapolate adevice-to-tissue distance d_(t) from the surgical device 502 to thesurface 505 of the uterus 503 based on the emitter-to-tissue distanced_(e). The surgical visualization system 500 is also configured todetermine a tissue-to-ureter distance d_(A) from the ureter 501 a to thesurface 505 and a camera-to ureter distance d_(w) from the imagingdevice 520 to the ureter 501 a. As described herein with respect to FIG.1 , for example, the surgical visualization system 500 can determine thedistance d_(w) with spectral imaging and time-of-flight sensors, forexample. In various instances, the surgical visualization system 500 candetermine (e.g. triangulate) the tissue-to-ureter distance d_(A) (ordepth) based on other distances and/or the surface mapping logicdescribed herein.

Referring now to FIG. 11 , where a schematic of a control system 600 fora surgical visualization system, such as the surgical visualizationsystem 100, for example, is depicted. The control system 600 is aconversion system that integrates spectral signature tissueidentification and structured light tissue positioning to identifycritical structures, especially when those structures are obscured byother tissue, such as fat, connective tissue, blood, and/or otherorgans, for example. Such technology could also be useful for detectingtissue variability, such as differentiating tumors and/or non-healthytissue from healthy tissue within an organ.

The control system 600 is configured for implementing a hyperspectralimaging and visualization system in which a molecular response isutilized to detect and identify anatomy in a surgical field of view. Thecontrol system 600 includes a conversion logic circuit 648 to converttissue data to surgeon usable information. For example, the variablereflectance based on wavelengths with respect to obscuring material canbe utilized to identify the critical structure in the anatomy. Moreover,the control system 600 combines the identified spectral signature andthe structural light data in an image. For example, the control system600 can be employed to create of three-dimensional data set for surgicaluse in a system with augmentation image overlays. Techniques can beemployed both intraoperatively and preoperatively using additionalvisual information. In various instances, the control system 600 isconfigured to provide warnings to a clinician when in the proximity ofone or more critical structures. Various algorithms can be employed toguide robotic automation and semi-automated approaches based on thesurgical procedure and proximity to the critical structure(s).

A projected array of lights is employed to determine tissue shape andmotion intraoperatively. Alternatively, flash Lidar may be utilized forsurface mapping of the tissue.

The control system 600 is configured to detect the critical structure(s)and provide an image overlay of the critical structure and measure thedistance to the surface of the visible tissue and the distance to theembedded/buried critical structure(s). In other instances, the controlsystem 600 can measure the distance to the surface of the visible tissueor detect the critical structure(s) and provide an image overlay of thecritical structure.

The control system 600 includes a spectral control circuit 602. Thespectral control circuit 602 can be a field programmable gate array(FPGA) or another suitable circuit configuration as described herein inconnection with FIGS. 2A-2C, for example. The spectral control circuit602 includes a processor 604 to receive video input signals from a videoinput processor 606. The processor 604 can be configured forhyperspectral processing and can utilize C/C++ code, for example. Thevideo input processor 606 receives video-in of control (metadata) datasuch as shutter time, wave length, and sensor analytics, for example.The processor 604 is configured to process the video input signal fromthe video input processor 606 and provide a video output signal to avideo output processor 608, which includes a hyperspectral video-out ofinterface control (metadata) data, for example. The video outputprocessor 608 provides the video output signal to an image overlaycontroller 610.

The video input processor 606 is coupled to a camera 612 at the patientside via a patient isolation circuit 614. As previously discussed, thecamera 612 includes a solid state image sensor 634. The patientisolation circuit can include a plurality of transformers so that thepatient is isolated from other circuits in the system. The camera 612receives intraoperative images through optics 632 and the image sensor634. The image sensor 634 can include a CMOS image sensor, for example,or may include any of the image sensor technologies discussed herein inconnection with FIG. 2 , for example. In one aspect, the camera 612outputs images in 14 bit/pixel signals. It will be appreciated thathigher or lower pixel resolutions may be employed without departing fromthe scope of the present disclosure. The isolated camera output signal613 is provided to a color RGB fusion circuit 616, which employs ahardware register 618 and a Nios2 co-processor 620 to process the cameraoutput signal 613. A color RGB fusion output signal is provided to thevideo input processor 606 and a laser pulsing control circuit 622.

The laser pulsing control circuit 622 controls a laser light engine 624.The laser light engine 624 outputs light in a plurality of wavelengths(λ₁, λ₂, λ₃ . . . λ_(n)) including near infrared (NIR). The laser lightengine 624 can operate in a plurality of modes. In one aspect, the laserlight engine 624 can operate in two modes, for example. In a first mode,e.g. a normal operating mode, the laser light engine 624 outputs anilluminating signal. In a second mode, e.g. an identification mode, thelaser light engine 624 outputs RGBG and NIR light. In various instances,the laser light engine 624 can operate in a polarizing mode.

Light output 626 from the laser light engine 624 illuminates targetedanatomy in an intraoperative surgical site 627. The laser pulsingcontrol circuit 622 also controls a laser pulse controller 628 for alaser pattern projector 630 that projects a laser light pattern 631,such as a grid or pattern of lines and/or dots, at a predeterminedwavelength (λ₂) on the operative tissue or organ at the surgical site627. The camera 612 receives the patterned light as well as thereflected light output through the camera optics 632. The image sensor634 converts the received light into a digital signal.

The color RGB fusion circuit 616 also outputs signals to the imageoverlay controller 610 and a video input module 636 for reading thelaser light pattern 631 projected onto the targeted anatomy at thesurgical site 627 by the laser pattern projector 630. A processingmodule 638 processes the laser light pattern 631 and outputs a firstvideo output signal 640 representative of the distance to the visibletissue at the surgical site 627. The data is provided to the imageoverlay controller 610. The processing module 638 also outputs a secondvideo signal 642 representative of a three-dimensional rendered shape ofthe tissue or organ of the targeted anatomy at the surgical site.

The first and second video output signals 640, 642 include datarepresentative of the position of the critical structure on athree-dimensional surface model, which is provided to an integrationmodule 643. In combination with data from the video out processor 608 ofthe spectral control circuit 602, the integration module 643 candetermine the distance d_(A) (FIG. 1 ) to a buried critical structure(e.g. via triangularization algorithms 644), and the distance d_(A) canbe provided to the image overlay controller 610 via a video outprocessor 646. The foregoing conversion logic can encompass theconversion logic circuit 648 intermediate video monitors 652 and thecamera 624/laser pattern projector 630 positioned at the surgical site627.

Preoperative data 650 from a CT or MRI scan can be employed to registeror align certain three-dimensional deformable tissue in variousinstances. Such preoperative data 650 can be provided to the integrationmodule 643 and ultimately to the image overlay controller 610 so thatsuch information can be overlaid with the views from the camera 612 andprovided to the video monitors 652. Registration of preoperative data isfurther described herein and in the aforementionedcontemporaneously-filed U.S. patent applications, including U.S. patentapplication Ser. No. 16/128,195, titled INTEGRATION OF IMAGING DATA, nowU.S. Patent Application Publication No. 2020/0015907, for example, whichare incorporated by reference herein in their respective entireties.

The video monitors 652 can output the integrated/augmented views fromthe image overlay controller 610. A clinician can select and/or togglebetween different views on one or more monitors. On a first monitor 652a, the clinician can toggle between (A) a view in which athree-dimensional rendering of the visible tissue is depicted and (B) anaugmented view in which one or more hidden critical structures aredepicted over the three-dimensional rendering of the visible tissue. Ona second monitor 652 b, the clinician can toggle on distancemeasurements to one or more hidden critical structures and/or thesurface of visible tissue, for example.

The control system 600 and/or various control circuits thereof can beincorporated into various surgical visualization systems disclosedherein.

FIG. 12 illustrates a structured (or patterned) light system 700,according to at least one aspect of the present disclosure. As describedherein, structured light in the form of stripes or lines, for example,can be projected from a light source and/or projector 706 onto thesurface 705 of targeted anatomy to identify the shape and contours ofthe surface 705. A camera 720, which can be similar in various respectsto the imaging device 120 (FIG. 1 ), for example, can be configured todetect the projected pattern of light on the surface 705. The way thatthe projected pattern deforms upon striking the surface 705 allowsvision systems to calculate the depth and surface information of thetargeted anatomy.

In certain instances, invisible (or imperceptible) structured light canbe utilized, in which the structured light is used without interferingwith other computer vision tasks for which the projected pattern may beconfusing. For example, infrared light or extremely fast frame rates ofvisible light that alternate between two exact opposite patterns can beutilized to prevent interference. Structured light is further describedat en.wikipedia.org/wiki/Structured_light

Referring now to FIG. 13 , by way example to illustrate the concept ofhyperspectral imaging, a terrestrial hyperspectral imaging system 800 isshown. The terrestrial hyperspectral imaging system 800 is configured toimage terrestrial features or objects, such as soil, water, and/orvegetation, for example. The terrestrial hyperspectral imaging system700 includes a space-borne hyperspectral sensor 822 on a spacecraft 820to conduct hyperspectral imaging of a portion of the Earth's surface805. The spectral dimension includes several layers. Each pixel of theimages contains a sampled spectrum that is used to identify thematerials present in the pixel by their reflectance. The data can beconverted to graphical representations 850, 852, 854 of reflectance as afunction of wavelength for soil, water, and vegetation, respectively,for example. Terrestrial hyperspectral imaging is further described atwww.markelowitz.com/Hyperspectral.html.

Also by way example to illustrate the concept of hyperspectral imaging,FIG. 14 is a graphical representation 850 of hyperspectral signaturesfor various terrestrial features or objects, according to at least oneaspect of the present disclosure. Percent reflectance is shown along thevertical axis and wavelength (nm) is shown along the horizontal axis. Asshown, each object—pinewoods, grasslands, red sand pit, and siltywater—has a unique hyperspectral signature that can be used to identifythe object.

The hyperspectral imaging concepts described in connection with FIGS. 13and 14 may be employed for different materials that have differentwavelengths and bands of absorption, according to at least one aspect ofthe present disclosure. The following table illustrates the wavelengthsand bands of absorption for various materials. A first range ofwavelengths between 400 nm and 700 nm represents the visible lightspectrum. A second range of wavelengths between 700 nm and 1400 nmrepresents the near infrared (NIR) spectrum. A third range ofwavelengths between 1400 nm and 3000 nm represents a shortwave infrared(SWIR) spectrum. A first band centered at 1250 nm represents ironabsorption and leaf moisture content. A second band between 1500 nm and1750 nm represents plastics, fiberglass, and petroleum. A third bandbetween 200 nm and 2400 nm represents mineral ID.

TABLE 1 specifies wavelengths and bands of absorption for variousmaterials.

TABLE 1 Wavelength (nm) Region Band(s) Material 400-700 Visible 700-1400 NIR 1400-3000 SWIR 1 - centered at 1250 Iron adsorption Leafmoisture content 2 - 1500-1750 Plastics Fiberglass Petroleum 3 -200-2400 nm Mineral ID

Referring now to FIGS. 15A-15C, as a further illustration ofhyperspectral imaging concepts, tests were conducted in which spectralimaging was applied to a fried egg 952. An image of the fried egg 952with a yellow egg yolk 954 and an egg white 956 surrounding the egg yolk954 is shown in FIG. 15A. A graphical representation 950 of spectralsignatures for the fried egg 952 are shown in FIG. 15B. Specifically,the graphical representation 950 shows absorption units versuswavelength (nm) for the egg yolk 954 and the egg white 956 of the friedegg 952. In FIG. 15C, a spectral image (in black-and-white) of the friedegg 952 is shown, in which the image is augmented to differentiatebetween the egg yolk portion and the egg white portion based on thehyperspectral signature data.

In various instances, hyperspectral imaging technology, as describedherein for illustrative purposes with respect to terrestrial featuresand objects and a fried egg, can be employed to identify signatures inanatomical structures in order to differentiate a critical structurefrom obscurants. Hyperspectral imaging technology may provide avisualization system that can provide a way to identify criticalstructures such as ureters and/or blood vessels, for example, especiallywhen those structures are obscured by fat, connective tissue, blood, orother organs, for example. The use of the difference in reflectance ofdifferent wavelengths in the infrared (IR) spectrum may be employed todetermine the presence of key structures versus obscurants. Referringnow to FIGS. 16-18 , illustrative hyperspectral signatures for a ureter,an artery, and nerve tissue with respect to obscurants such as fat, lungtissue, and blood, for example, are depicted.

FIG. 16 is a graphical representation 1050 of an illustrative uretersignature versus obscurants. The plots represent reflectance as afunction of wavelength (nm) for wavelengths for fat, lung tissue, blood,and a ureter. FIG. 17 is a graphical representation 1052 of anillustrative artery signature versus obscurants. The plots representreflectance as a function of wavelength (nm) for fat, lung tissue,blood, and a vessel. FIG. 18 is a graphical representation 1054 of anillustrative nerve signature versus obscurants. The plots representreflectance as a function of wavelength (nm) for fat, lung tissue,blood, and a nerve.

In various instances, select wavelengths for spectral imaging can beidentified and utilized based on the anticipated critical structuresand/or obscurants at a surgical site (i.e. “selective spectral”imaging). By utilizing selective spectral imaging, the amount of timerequired to obtain the spectral image can be minimized such that theinformation can be obtained in real-time, or near real-time, andutilized intraoperatively. In various instances, the wavelengths can beselected by a clinician or by a control circuit based on input by theclinician. In certain instances, the wavelengths can be selected basedon machine learning and/or big data accessible to the control circuitvia a cloud, for example.

The foregoing application of spectral imaging to tissue can be utilizedintraoperatively to measure the distance between a waveform emitter anda critical structure that is obscured by tissue. In one aspect of thepresent disclosure, referring now to FIGS. 19 and 20 , a time-of-flightsensor system 1104 utilizing waveforms 1124, 1125 is shown. Thetime-of-flight sensor system 1104 can be incorporated into the surgicalvisualization system 100 (FIG. 1 ) in certain instances. Thetime-of-flight sensor system 1104 includes a waveform emitter 1106 and awaveform receiver 1108 on the same surgical device 1102. The emittedwave 1124 extends to the critical structure 1101 from the emitter 1106and the received wave 1125 is reflected back to by the receiver 1108from the critical structure 1101. The surgical device 1102 is positionedthrough a trocar 1110 that extends into a cavity 1107 in a patient.

The waveforms 1124, 1125 are configured to penetrate obscuring tissue1103. For example, the wavelengths of the waveforms 1124, 1125 can be inthe NIR or SWIR spectrum of wavelengths. In one aspect, a spectralsignal (e.g. hyperspectral, multispectral, or selective spectral) or aphotoacoustic signal can be emitted from the emitter 1106 and canpenetrate the tissue 1103 in which the critical structure 1101 isconcealed. The emitted waveform 1124 can be reflected by the criticalstructure 1101. The received waveform 1125 can be delayed due to thedistance d between the distal end of the surgical device 1102 and thecritical structure 1101. In various instances, the waveforms 1124, 1125can be selected to target the critical structure 1101 within the tissue1103 based on the spectral signature of the critical structure 1101, asfurther described herein. In various instances, the emitter 1106 isconfigured to provide a binary signal on and off, as shown in FIG. 20 ,for example, which can be measured by the receiver 1108.

Based on the delay between the emitted wave 1124 and the received wave1125, the time-of-flight sensor system 1104 is configured to determinethe distance d (FIG. 19 ). A time-of-flight timing diagram 1130 for theemitter 1106 and the receiver 1108 of FIG. 19 is shown in FIG. 20 . Thedelay is a function of the distance d and the distance d is given by:

$d = {\frac{ct}{2} \cdot \frac{q_{2}}{q_{1} + q_{2}}}$

where:

c=the speed of light;

t=length of pulse;

q₁=accumulated charge while light is emitted; and

q₂=accumulated charge while light is not being emitted.

As provided herein, the time-of-flight of the waveforms 1124, 1125corresponds to the distance din FIG. 19 . In various instances,additional emitters/receivers and/or pulsing signals from the emitter1106 can be configured to emit a non-penetrating signal. Thenon-penetrating tissue can be configured to determine the distance fromthe emitter to the surface 1105 of the obscuring tissue 1103. In variousinstances, the depth of the critical structure 1101 can be determinedby:

d _(A) =d _(w) −d _(t).

where:

d_(A)=the depth of the critical structure 1101;

d_(w)=the distance from the emitter 1106 to the critical structure 1101(din FIG. 19 ); and

d_(t)=the distance from the emitter 1106 (on the distal end of thesurgical device 1102) to the surface 1105 of the obscuring tissue 1103.

In one aspect of the present disclosure, referring now to FIG. 21 , atime-of-flight sensor system 1204 utilizing waves 1224 a, 1224 b, 1224c, 1225 a, 1225 b, 1225 c is shown. The time-of-flight sensor system1204 can be incorporated into the surgical visualization system 100(FIG. 1 ) in certain instances. The time-of-flight sensor system 1204includes a waveform emitter 1206 and a waveform receiver 1208. Thewaveform emitter 1206 is positioned on a first surgical device 1202 a,and the waveform receiver 1208 is positioned on a second surgical device1202 b. The surgical devices 1202 a, 1202 b are positioned through theirrespective trocars 1210 a, 1210 b, respectively, which extend into acavity 1207 in a patient. The emitted waves 1224 a, 1224 b, 1224 cextend toward a surgical site from the emitter 1206 and the receivedwaves 1225 a, 1225 b, 1225 c are reflected back to the receiver 1208from various structures and/or surfaces at the surgical site.

The different emitted waves 1224 a, 1224 b, 1224 c are configured totarget different types of material at the surgical site. For example,the wave 1224 a targets the obscuring tissue 1203, the wave 1224 btargets a first critical structure 1201 a (e.g. a vessel), and the wave1224 c targets a second critical structure 1201 b (e.g. a canceroustumor). The wavelengths of the waves 1224 a, 1224 b, 1224 c can be inthe visible light, NIR, or SWIR spectrum of wavelengths. For example,visible light can be reflected off a surface 1205 of the tissue 1203 andNIR and/or SWIR waveforms can be configured to penetrate the surface1205 of the tissue 1203. In various aspects, as described herein, aspectral signal (e.g. hyperspectral, multispectral, or selectivespectral) or a photoacoustic signal can be emitted from the emitter1206. In various instances, the waves 1224 b, 1224 c can be selected totarget the critical structures 1201 a, 1201 b within the tissue 1203based on the spectral signature of the critical structure 1201 a, 1201b, as further described herein. Photoacoustic imaging is furtherdescribed herein and in the aforementioned contemporaneously-filed U.S.patent applications, which are incorporated by reference herein in theirrespective entireties.

The emitted waves 1224 a, 1224 b, 1224 c can be reflected off thetargeted material (i.e. the surface 1205, the first critical structure1201 a, and the second structure 1201 b, respectively). The receivedwaveforms 1225 a, 1225 b, 1225 c can be delayed due to the distancesd_(1a), d_(2a), d_(3a), d_(1b), d_(2b), d_(2c) indicated in FIG. 21 .

In the time-of-flight sensor system 1204, in which the emitter 1206 andthe receiver 1208 are independently positionable (e.g., on separatesurgical devices 1202 a, 1202 b and/or controlled by separate roboticarms), the various distances d_(1a), d_(2a), d_(3a), d_(1b), d_(2b),d_(2c) can be calculated from the known position of the emitter 1206 andthe receiver 1208. For example, the positions can be known when thesurgical devices 1202 a, 1202 b are robotically-controlled. Knowledge ofthe positions of the emitter 1206 and the receiver 1208, as well as thetime of the photon stream to target a certain tissue and the informationreceived by the receiver 1208 of that particular response can allow adetermination of the distances d_(1a), d_(2a), d_(3a), d_(1b), d_(2b),d_(2c). In one aspect, the distance to the obscured critical structures1201 a, 1201 b can be triangulated using penetrating wavelengths.Because the speed of light is constant for any wavelength of visible orinvisible light, the time-of-flight sensor system 1204 can determine thevarious distances.

Referring still to FIG. 21 , in various instances, in the view providedto the clinician, the receiver 1208 can be rotated such that the centerof mass of the target structure in the resulting images remainsconstant, i.e., in a plane perpendicular to the axis of a select targetstructures 1203, 1201 a, or 1201 b. Such an orientation can quicklycommunicate one or more relevant distances and/or perspectives withrespect to the critical structure. For example, as shown in FIG. 21 ,the surgical site is displayed from a viewpoint in which the criticalstructure 1201 a is perpendicular to the viewing plane (i.e. the vesselis oriented in/out of the page). In various instances, such anorientation can be default setting; however, the view can be rotated orotherwise adjusted by a clinician. In certain instances, the cliniciancan toggle between different surfaces and/or target structures thatdefine the viewpoint of the surgical site provided by the imagingsystem.

In various instances, the receiver 1208 can be mounted on a trocar orcannula, such as the trocar 1210 b, for example, through which thesurgical device 1202 b is positioned. In other instances, the receiver1208 can be mounted on a separate robotic arm for which thethree-dimensional position is known. In various instances, the receiver1208 can be mounted on a movable arm that is separate from the robotthat controls the surgical device 1202 a or can be mounted to anoperating room (OR) table that is intraoperatively registerable to therobot coordinate plane. In such instances, the position of the emitter1206 and the receiver 1208 can be registerable to the same coordinateplane such that the distances can be triangulated from outputs from thetime-of-flight sensor system 1204.

Combining time-of-flight sensor systems and near-infrared spectroscopy(NIRS), termed TOF-NIRS, which is capable of measuring the time-resolvedprofiles of NIR light with nanosecond resolution can be found in thearticle titled TIME-OF-FLIGHT NEAR-INFRARED SPECTROSCOPY FORNONDESTRUCTIVE MEASUREMENT OF INTERNAL QUALITY IN GRAPEFRUIT, in theJournal of the American Society for Horticultural Science, May 2013 vol.138 no. 3 225-228, which is incorporated by reference herein in itsentirety, and is accessible atjournal.ashspublications.org/content/138/3/225.full.

In various instances, time-of-flight spectral waveforms are configuredto determine the depth of the critical structure and/or the proximity ofa surgical device to the critical structure. Moreover, the varioussurgical visualization systems disclosed herein include surface mappinglogic that is configured to create three-dimensional rendering of thesurface of the visible tissue. In such instances, even when the visibletissue obstructs a critical structure, the clinician can be aware of theproximity (or lack thereof) of a surgical device to the criticalstructure. In one instances, the topography of the surgical site isprovided on a monitor by the surface mapping logic. If the criticalstructure is close to the surface of the tissue, spectral imaging canconvey the position of the critical structure to the clinician. Forexample, spectral imaging may detect structures within 5 or 10 mm of thesurface. In other instances, spectral imaging may detect structures 10or 20 mm below the surface of the tissue. Based on the known limits ofthe spectral imaging system, the system is configured to convey that acritical structure is out-of-range if it is simply not detected by thespectral imaging system. Therefore, the clinician can continue to movethe surgical device and/or manipulate the tissue. When the criticalstructure moves into range of the spectral imaging system, the systemcan identify the structure and, thus, communicate that the structure iswithin range. In such instances, an alert can be provided when astructure is initially identified and/or moved further within apredefined proximity zone. In such instances, even non-identification ofa critical structure by a spectral imaging system with knownbounds/ranges can provide proximity information (i.e. the lack ofproximity) to the clinician.

Various surgical visualization systems disclosed herein can beconfigured to identify intraoperatively the presence of and/or proximityto critical structure(s) and to alert a clinician prior to damaging thecritical structure(s) by inadvertent dissection and/or transection. Invarious aspects, the surgical visualization systems are configured toidentify one or more of the following critical structures: ureters,bowel, rectum, nerves (including the phrenic nerve, recurrent laryngealnerve [RLN], promontory facial nerve, vagus nerve, and branchesthereof), vessels (including the pulmonary and lobar arteries and veins,inferior mesenteric artery [IMA] and branches thereof, superior rectalartery, sigmoidal arteries, and left colic artery), superior mesentericartery (SMA) and branches thereof (including middle colic artery, rightcolic artery, ilecolic artery), hepatic artery and branches thereof,portal vein and branches thereof, splenic artery/vein and branchesthereof, external and internal (hypogastric) ileac vessels, shortgastric arteries, uterine arteries, middle sacral vessels, and lymphnodes, for example. Moreover, the surgical visualization systems areconfigured to indicate proximity of surgical device(s) to the criticalstructure(s) and/or warn the clinician when surgical device(s) aregetting close to the critical structure(s).

Various aspects of the present disclosure provide intraoperativecritical structure identification (e.g., identification of ureters,nerves, and/or vessels) and instrument proximity monitoring. Forexample, various surgical visualization systems disclosed herein caninclude spectral imaging and surgical instrument tracking, which enablethe visualization of critical structures below the surface of thetissue, such as 1.0-1.5 cm below the surface of the tissue, for example.In other instances, the surgical visualization system can identifystructures less than 1.0 cm or more the 1.5 cm below the surface of thetissue. For example, even a surgical visualization system that canidentify structures only within 0.2 mm of the surface, for example, canbe valuable if the structure cannot otherwise be seen due to the depth.In various aspects, the surgical visualization system can augment theclinician's view with a virtual depiction of the critical structure as avisible white-light image overlay on the surface of visible tissue, forexample. The surgical visualization system can provide real-time,three-dimensional spatial tracking of the distal tip of surgicalinstruments and can provide a proximity alert when the distal tip of asurgical instrument moves within a certain range of the criticalstructure, such as within 1.0 cm of the critical structure, for example.

Various surgical visualization systems disclosed herein can identifywhen dissection is too close to a critical structure. Dissection may be“too close” to a critical structure based on the temperature (i.e. toohot within a proximity of the critical structure that may riskdamaging/heating/melting the critical structure) and/or based on tension(i.e. too much tension within a proximity of the critical structure thatmay risk damaging/tearing/pulling the critical structure). Such asurgical visualization system can facilitate dissection around vesselswhen skeletonizing the vessels prior to ligation, for example. Invarious instances, a thermal imaging camera can be utilized to read theheat at the surgical site and provide a warning to the clinician that isbased on the detected heat and the distance from a tool to thestructure. For example, if the temperature of the tool is over apredefined threshold (such as 120 degrees F., for example), an alert canbe provided to the clinician at a first distance (such as 10 mm, forexample), and if the temperature of the tool is less than or equal tothe predefined threshold, the alert can be provided to the clinician ata second distance (such as 5 mm, for example). The predefined thresholdsand/or warning distances can be default settings and/or programmable bythe clinician. Additionally or alternatively, a proximity alert can belinked to thermal measurements made by the tool itself, such as athermocouple that measures the heat in a distal jaw of a monopolar orbipolar dissector or vessel sealer, for example.

Various surgical visualization systems disclosed herein can provideadequate sensitivity with respect to a critical structure andspecificity to enable a clinician to proceed with confidence in a quickbut safe dissection based on the standard of care and/or device safetydata. The system can function intraoperatively and in real-time during asurgical procedure with minimal ionizing radiation risk to a patient ora clinician and, in various instances, no risk of ionizing radiationrisk to the patient or the clinician. Conversely, in a fluoroscopyprocedure, the patient and clinician(s) may be exposed to ionizingradiation via an X-ray beam, for example, that is utilized to view theanatomical structures in real-time.

Various surgical visualization system disclosed herein can be configuredto detect and identify one or more desired types of critical structuresin a forward path of a surgical device, such as when the path of thesurgical device is robotically controlled, for example. Additionally oralternatively, the surgical visualization system can be configured todetect and identify one or more types of critical structures in asurrounding area of the surgical device and/or in multipleplanes/dimensions, for example.

Various surgical visualization systems disclosed herein can be easy tooperate and/or interpret. Moreover, various surgical visualizationsystems can incorporate an “override” feature that allows the clinicianto override a default setting and/or operation. For example, a cliniciancan selectively turn off alerts from the surgical visualization systemand/or get closer to a critical structure than suggested by the surgicalvisualization system such as when the risk to the critical structure isless than risk of avoiding the area (e.g. when removing cancer around acritical structure the risk of leaving the cancerous tissue can begreater than the risk of damage to the critical structure).

Various surgical visualization systems disclosed herein can beincorporated into a surgical system and/or used during a surgicalprocedure with limited impact to the workflow. In other words,implementation of the surgical visualization system may not change theway the surgical procedure is implemented. Moreover, the surgicalvisualization system can be economical in comparison to the costs of aninadvertent transection. Data indicates the reduction in inadvertentdamage to a critical structure can drive incremental reimbursement.

Various surgical visualization systems disclosed herein can operate inreal-time, or near real-time, and far enough in advance to enable aclinician to anticipate critical structure(s). For example, a surgicalvisualization system can provide enough time to “slow down, evaluate,and avoid” in order to maximize efficiency of the surgical procedure.

Various surgical visualization systems disclosed herein may not requirea contrast agent, or dye, that is injected into tissue. For example,spectral imaging is configured to visualize hidden structuresintraoperatively without the use of a contrast agent or dye. In otherinstances, the contrast agent can be easier to inject into the properlayer(s) of tissue than other visualization systems. The time betweeninjection of the contrast agent and visualization of the criticalstructure can be less than two hours, for example.

Various surgical visualization systems disclosed herein can be linkedwith clinical data and/or device data. For example, data can provideboundaries for how close energy-enabled surgical devices (or otherpotentially damaging devices) should be from tissue that the surgeondoes not want to damage. Any data modules that interface with thesurgical visualization systems disclosed herein can be providedintegrally or separately from a robot to enable use with stand-alonesurgical devices in open or laparoscopic procedures, for example. Thesurgical visualization systems can be compatible with robotic surgicalsystems in various instances. For example, the visualizationimages/information can be displayed in a robotic console.

Example Clinical Applications

Various surgical visualization systems disclosed herein may be employedin one or more of the following clinical applications. The followingclinical applications are non-exhaustive and merely illustrativeapplications for one or more of the various surgical visualizationsystems disclosed herein.

A surgical visualization system, as disclosed herein, can be employed ina number of different types of procedures for different medicalspecialties, such as urology, gynecology, oncology, colorectal,thoracic, bariatric/gastric, and hepato-pancreato-biliary (HPB), forexample. In urological procedures, such as a prostatectomy, for example,the ureter may be detected in fat or connective tissue and/or nerves maybe detected in fat, for example. In gynecological oncology procedures,such as a hysterectomy, for example, and in colorectal procedures, suchas a low anterior resection (LAR) procedure, for example, the ureter maybe detected in fat and/or in connective tissue, for example. In thoracicprocedures, such as a lobectomy, for example, a vessel may be detectedin the lung or in connective tissue and/or a nerve may be detected inconnective tissue (e.g., an esophagostomy). In bariatric procedures, avessel may be detected in fat. In HPB procedures, such as a hepatectomyor pancreatectomy, for example, a vessel may be detected in fat(extrahepatic), in connective tissue (extrahepatic), and the bile ductmay be detected in parenchyma (liver or pancreas) tissue.

In one example, a clinician may want to remove an endometrial myoma.From a preoperative magnetic resonance imaging (MRI) scan, the clinicianmay know that the endometrial myoma is located on the surface of thebowel. Therefore, the clinician may want to know, intraoperatively, whattissue constitute a portion of the bowel and what tissue constitutes aportion of the rectum. In such instances, a surgical visualizationsystem, as disclosed herein, can indicate the different types of tissue(bowel versus rectum) and convey that information to a clinician via animaging system. Moreover, the imaging system can determine andcommunicate the proximity of a surgical device to the select tissue. Insuch instances, the surgical visualization system can provide increasedprocedural efficiency without critical complications.

In another example, a clinician (e.g. a gynecologist) may stay away fromcertain anatomic regions to avoid getting too close to criticalstructures and, thus, the clinician may not remove all of theendometriosis, for example. A surgical visualization system, asdisclosed herein, can enable the gynecologist to mitigate the risk ofgetting too close to the critical structure such that the gynecologistcan get close enough with the surgical device to remove all theendometriosis, which can improve the patient outcomes (democratizingsurgery). Such a system can enable the surgeon to “keep moving” duringthe surgical procedure instead of repeatedly stopping and restarting inorder to identify areas to avoid, especially during the application oftherapeutic energy such as ultrasonic or electrosurgical energy, forexample. In gynecological applications, uterine arteries and ureters areimportant critical structures and the system may be particularly usefulfor hysterectomy and endometriosis procedures given the presentationand/or thickness of tissue involved.

In another example, a clinician may risk dissection of a vessel at alocation that is too proximal and, thus, which can affect blood supplyto a lobe other than the target lobe. Moreover, anatomic differencesfrom patient to patient may lead to dissection of a vessel (e.g. abranch) that affects a different lobe based on the particular patient. Asurgical visualization system, as disclosed herein, can enable theidentification of the correct vessel at the desired location, whichenables the clinician to dissect with appropriate anatomic certainty.For example, the system can confirm that the correct vessel is in thecorrect place and then the clinician can safely divide the vessel.

In another example, a clinician may make multiple dissections beforedissecting at the best location due to uncertainty about the anatomy ofthe vessel. However, it is desirable to dissect in the best location inthe first instance because more dissection can increase the risk ofbleeding. A surgical visualization system, as disclosed herein, canminimize the number of dissections by indicating the correct vessel andthe best location for dissection. Ureters and cardinal ligaments, forexample, are dense and provide unique challenges during dissection. Insuch instances, it can be especially desirable to minimize the number ofdissections.

In another example, a clinician (e.g. a surgical oncologist) removingcancerous tissue may want to know the identification of criticalstructures, localization of the cancer, staging of the cancer, and/or anevaluation of tissue health. Such information is beyond what a cliniciansees with the “naked eye”. A surgical visualization system, as disclosedherein, can determine and/or convey such information to the clinicianintraoperatively to enhance intraoperative decision making and improvesurgical outcomes. In certain instances, the surgical visualizationsystem can be compatible with minimally invasive surgery (MIS), opensurgery, and/or robotic approaches using either an endoscope orexoscope, for example.

In another example, a clinician (e.g. a surgical oncologist) may want toturn off one or more alerts regarding the proximity of a surgical toolto one or more critical structure to avoid being overly conservativeduring a surgical procedure. In other instances, the clinician may wantto receive certain types of alerts, such as haptic feedback (e.g.vibrations/buzzing) to indicate proximity and/or or “no fly zones” tostay sufficiently far away from one or more critical structures. Asurgical visualization system, as disclosed herein, can provideflexibility based on the experience of the clinician and/or desiredaggressiveness of the procedure, for example. In such instances, thesystem provides a balance between “knowing too much” and “knowingenough” to anticipate and avoid critical structures. The surgicalvisualization system can assist in planning the next step(s) during asurgical procedure.

The systems, methods, devices, and control circuits discussed herein canalso benefit and be used in a surgical suturing environment. Morespecifically, the surgical visualization systems can benefit surgicalsuturing systems. A clinician suturing tissue manually, robotically,and/or manually and robotically, can utilize such surgical visualizationsystems in a surgical suturing environment to help prevent contacting,puncturing, and/or scraping, for example, of an embedded structure witha suturing needle. In certain instances, the surgical visualizationsystems can be used to monitor the position of a needle in addition tothe position of a critical structure. Discussed in greater detail below,surgical suturing systems utilizing such surgical visualization systemscan monitor and/or track the relative position between a suturing needleand one or more embedded structures in real time, for example, and canalert a clinician and/or automatically adjust operation of a robot thatmay be assisting the suturing procedure, for example, if the needle getstoo close to a embedded structure. Other surgical suturing systems arecapable of predicting the path of a needle based on an initial startingpoint and comparing that path to detected embedded structures. Suchsystems can also recommend a different starting point and/or alert aclinician that the predicted suturing path to be preformed roboticallymay interfere with an embedded structure, for example.

In various instances, a system and method for robotically assistedsuturing with indication of needle proximity to a critical structure isprovided. The system and method are configured to prevent a sutureneedle from contacting a critical structure during robotic surgery. Thesystem and method provide a technique for programing a suture needledriver, such as a grasper, for example, to perform repetitive portionsof the suturing process.

FIG. 22 depicts a surgical suturing system 5700. The surgical suturingsystem 5700 comprises a grasper 5701, a surgical visualization assembly5702 including a sensor and an emitter, and a suturing assemblycomprising a needle 5703 and suturing material 5705 attached theretoconfigured to suture tissue T. The grasper 5701 is configured to actuatethe needle 5703 through a complete suturing stroke by puncturing thesurface of the tissue T with a tip 5704 of the needle 5703, crossing thegap 5706 of the tissue T, and causing the tip 5704 of the needle 5703 topuncture back out through the surface of the tissue T.

The grasper 5701 may be a part of a robotic system, for example, and canbe actuated manually through the robot by an operator and/orautomatically through the robot by a control program. As discussed ingreater detail below, a repetitive portion of a suturing motion may beautomated such as the suturing stroke. Such a robotic system can be seenin FIG. 1 , for example. The grasper 5701 may be actuated by a roboticarm of the robotic system 110. Further to the above, the controlcircuits discussed herein in connection with the surgical suturingsystems can be configured to operate the robotic system directly. Inother instances, the control circuits can be configured to sendinstructions to a control circuit of the robotic system itself. Theinstruments, components, devices, systems, and methods disclosed hereincan be used with the instruments, components, devices, systems, andmethods disclosed in U.S. Pat. No. 9,072,535, entitled SURGICAL STAPLINGINSTRUMENTS WITH ROTATABLE STAPLE DEPLOYMENT ARRANGEMENTS, which isincorporated by reference herein in its entirety.

As discussed above, the grasper 5701 may be robotically-assisted throughcertain control motions during a surgical suturing procedure. Forexample, the robotic system can be configured to rotate the grasperautomatically through the suturing stroke such that a clinician does nothave to perform the suturing stroke itself but, instead, may only berequired to align the grasper 5701 and the needle 5703 to perform eachsuturing stroke. In such instances, the clinician may place the tip 5704of the needle 5703 on the tissue to be sutured and then instruct therobot to initiate the suturing stroke sequence of the grasper 5701. Inother instances, the grasper 5701 may be manually operated throughoutthe entire suturing procedure. At any rate, as discussed in greaterdetail below, the surgical visualization assembly 5702 is configured tomonitor the position of the needle 5703, the grasper 5701, and/or anyembedded structures, such as the embedded structure 5707, during thesuturing procedure. The surgical visualization assembly 5702 may besimilar to that of any of the visualization systems discussed herein.The surgical visualization assembly 5702 may include a hyperspectralimaging device to image and visualize hidden, or embedded, criticaltissue structures. The hyperspectral imaging and visualization systemcan calculate the position of tissue structures, e.g., a vein hiddenbelow the surface of tissue in the illustrated example (FIG. 22 ),relative to a predicted suturing needle path or the suturing needleitself. The system can provide a warning, or alert, when the systemdetermines, or calculates, that the needle 5703 and/or the suturingstroke path of the needle 5703 and the embedded structure 5707 are tooclose to each other. The proximity that would warrant an alert may beselectable by a clinician before the suturing stroke is performed or maybe recommended based on data provided by relevant standards. Thedetermination process and control circuits for use with such surgicalsuturing tracking, or visualization, systems is explained in greaterdetail below.

FIG. 23 depicts a monitoring system 5710 displaying a surgical site,such as the one illustrated in FIG. 22 . The monitoring system 5710 isconfigured to display the suturing process performed by the surgicalsuturing system 5700 and is augmented with a side display 5711comprising a proximity indicator 5712. The side display 5711 comprises awarning zone and lights up when the suturing needle, and as a result theproximity indicator 5712, enters the warning zone. The monitoring system5719 is configured to reproduce the surgical site in a display format byusing the data collected by the surgical visualization assembly 5702.The monitoring system 5710 may use additional cameras and/or waveformsensors to replicate the surgical site on the display.

The monitoring system 5719 can further be configured to highlightvarious structures as different times. For example, if the proximitydetected between the needle 5703′ and the embedded structure is within acritical proximity, the embedded structure itself may be highlightedusing any suitable highlighting technique, e.g., change color,brightness, and/or pattern. Moreover, additional visual indicia may beoverlaid onto the displayed image to indicate to a clinician of apredicted suture path relative to an embedded structure. Such visualindicia may include an “X”, for example, where a predicted suturing pathof the needle may result in puncturing the embedded structure at thelocation marked with the “X”. Anything capable of being detected by thecameras and/or waveform sensors within the surgical site can behighlighted and/or monitored such as, for example, the suturing materialhidden or not hidden by tissue, the piercing tip of the needle, and/orthe grasper 5701′. The monitoring system 5719 may also predict where theneedle may exit the other side of the tissue gap and denote thislocation with some sort of visual indicia.

Still referring to FIG. 23 , the side display 5711 can be configured tomonitor the proximity of the needle and any critical structures or anydesired combination of components that a clinician would want to monitorthe relative proximity of. In various instances, the proximity of thetip of the needle and the embedded structure(s) are monitored and theclosest distance between the needle tip and the embedded structure isindicated by the indicator 5712. As the distance between the needle tipand the embedded structure changes, the indicator 5712 moves to indicatethis distance to a clinician. In various instances, zones can beprovided and/or selected by a clinician to alert the clinician when theproximity falls within each zone individually. For example, a first zonemay include a distance which is not critical to the clinician but isnoteworthy of being communicated to the surgeon on the display. Theclinician will be able to see that the indicator is in the first zoneand may be alerted of such information. A second zone indicating acloser proximity than the first may issue a visual and audible warningalerting the clinician that the indicator is in the second zone with aheightened alert relative to the first zone. If the proximity reachesthe second zone, a heightened alert may be initiated and may include,for example, a visual indication, an audible indication in the operatingsuite, and/or an adjust made to control motions being applied to therobot arm, for example, discussed in greater detail below. Zoningvarious levels of proximity is not limited to a display. Such a methodcan be used in a control circuit configured to control variouscomponents of the surgical suturing system such as, for example, therobot arm and/or the waveform sensor, among others.

In at least one aspect, hyperspectral imaging can visualize a metallicneedle when buried by tissue. By having critical structures identifiedby this system as well, the robotic system can indicate when thesuturing needle is within a certain proximity to the hidden criticalstructure. Given a point on a tissue surface that a surgeon selects, asystem can provide information regarding various components of theprocedure. For example, a control circuit can predict suture bite depthof a needle once placed on the surface of tissue. In such an instance,the suture bite depth of the needle can be calculated based on theposition of the robotic arm to which the grasper holding the needle isattached and can be conveyed to a clinician. In at least one instance,structured light can be used to monitor and/or track movement of thetissue surface. Structured light can also be used to detect when theneedle itself punctures through tissue and pokes back out of tissue bydetecting when the tissue surface and, thus, the structured lightpattern, is broken. A control circuit can also provide a recommendedsuture bite width for different tissues. In such an instance, the typeof tissue can be detected and identified and then compared to a lookuptable with predefined recommended suture bite widths. In at least oneinstance, a control circuit can break the suturing site into differentzones and indicate to a clinician what zones to avoid while suturing.Any of this information can be communicated to a clinician and/orautomatically fed into logic of a control circuit that controls any orall parts of a surgical suturing system. For example, a robotic systemcan automatically avoid a zone detected to be unsafe for suturingwithout indicating that this zone is restricted in any way to aclinician. Such a robotic system may prevent movement of its robotic armcomponents, for example, that would result in suturing a restrictedzone, for example.

In at least one instance, structured light can be used to track thesurface of tissue as it moves during a surgical suturing procedure. Forexample, a surgeon may select a starting point and/or location on thetissue surface for the suturing stroke to begin. This point would be thelocation for the needle to puncture the tissue and begin its suturingstroke. The grasper and, thus, the suturing needle may be automaticallymoved to this location by the robotic system and/or may be manuallymoved to this location by the clinician operating the robotic system.Before the tissue is actually punctured to begin the suturing stroke,the tissue and, thus, the surface of the tissue may move. If the surfaceof the tissue moves, it may be desirable to track this movement to trackthe movement of the location chosen for the beginning of the suturingstroke. The control system can interpret this data to automaticallyreposition the needle to where the chosen location has moved to and/oralert the clinician that the chosen location has moved. In at least oneinstance, the control circuit can provide updated information in realtime to the clinician regarding the suturing stroke. For example, thecontrol circuit can provide information such as and/or related to thecapture width of the needle and/or the depth that the needle will travelduring its suturing stroke.

FIGS. 24-26 illustrate a sequence of images that represent arobotically-assisted suturing motion utilizing a grasper 5721 connectedto a surgical robot and a suturing needle 5724 configured to suturetissue T. The robotically-assisted suturing motion can be performedautomatically by a robotic system. However, the full suturing operationmay comprise manual portions wear a clinician may operate a roboticsystem to which the grasper 5721 is attached manually and automaticportions wear a clinician initiates an automatic sequence instruction toinstruct the robotic system to perform that portion automatically. Suchan arrangement allows the robot to automate tedious and/or repetitiveportions of the suturing motion that, in at least one instance, areconstant in all suturing procedures.

Still referring to FIGS. 24-26 , the grasper 5721 comprises anarticulation joint 5722 and grasping jaws 923 extending therefromconfigured to be articulated and/or rotated relative to the shaft of thegrasper 5721. Such graspers are commonly used in robotic systems. Theneedle 5724 comprises suturing material 5726 attached to a trailing endof the needle 5724 and a piercing tip 5725 configured to pierce tissue Tand travel through the tissue T to install the suturing material 5726.FIG. 24 illustrates an initializing sequence of the robotically-assistedsuturing motion where a clinician manually touches suture needle 5724 tothe tissue T with a robotic arm, for example. Such an action mayinitiate the robotically-assisted suturing motion. In at least oneinstance, a waveform sensor and/or any suitable camera can detect thisposition and inform a control circuit that the portion of the suturingmotion that involves piercing and turning through tissue, also referredto as the suturing stroke, is ready to be performed. Once in thisposition, a clinician may press a button, for example, on the roboticsystem to initiate the suturing stroke. When the button is pressed, therobotic system will automatically perform the suturing stroke portion ofthe suturing procedure by manipulating its components, such as therobotic arm, so that the grasper will move in a fashion to perform thesuturing stroke. The motions applied to the grasper by the roboticsystem may vary between suturing strokes in the same procedure. Forexample, a camera may be used to map out the topography of the tissueand gather any other data from the surgical site for each suturingstroke. This information can be conveyed to a control circuit such thatthe robotic system can adjust its automated suturing stroke controlprogram such that the control motions applied to the grasper areadjusted to perform a proper suturing stroke in each specific location.Such an arrangement may be advantageous where the tissue being suturedis not level, or flat, and the grasper must be angled, and/or tilted, toaccommodate the topography. Of course, tissue may move during eachstroke and between strokes. Such an arrangement can help accommodateconstant tissue movement when data about the surgical site and,specifically, the tissue topography, for example, is conveyed in realtime.

After the automated portion of the suturing motion is performed, theneedle 5724 is in the location illustrated in FIG. 25 . In at least oneinstance, the automated suturing stroke can be adjusted before and/orthroughout the procedure based on clinician preference and/or any otherinformation, for example. At any rate, the needle 5724 is ready to bepulled through the tissue T to pull the suturing material 5726 throughthe tissue T. FIG. 26 illustrates the grasper 5721 holding, or grabbing,the tip 5725 of the needle 5724. In at least one instance, grabbing thetip of the needle is part of the automated portion of the suturingmotion. In another instance, grabbing the tip of the needle is notautomated and clinician must manually grab the tip of the needle withthe grasper. At any rate, the needle 5724 and, as a result, the suturingmaterial 5726 are pulled through the tissue T with the grasper 5721 tocomplete a cycle of the suturing motion. Multiple cycles of the suturingmotion can be performed depending on the clinician's suturing strategy.In instances where multiple cycles are performed, one or more cycles maycomprise automation while one more other cycles may be entirely manual.

Various types of control programs and/or circuits can be employed withthe devices and systems disclosed herein. FIG. 27 is a flowchartdepicting an algorithm, or process, 5730 configured to be executed by acontrol circuit utilizing a surgical visualization feedback system todetermine the relative position of a suturing needle and an embeddedtissue structure. Such a system may be referred to as a surgicalsuturing tracking, or guiding, system, for example. The process 5730comprises receiving an input 5731 to initiate the process 5730. Such aninput may comprise a physical button that the clinician can press and/ora sensed condition within the surgical site, for example. It should beappreciated that physical initiation of the process 5730 is notnecessary and that the algorithm can be initiated automatically by arobotic system. The process 5730 further comprises causing 5732 aspectral light emitter, such as those disclosed herein, to emit spectrallight waves toward a suturing needle and a tissue structure. Thisfunction permits the system to detect the location various componentswithin the surgical site such as, for example, the suturing needle andthe tissue structure. In at least one instance, the spectral lightemitter is configured to emit spectral light waves toward othercomponents in addition to or in lieu of the needle and the tissuestructure within the surgical site that are desired to be detected. Atany rate, whatever components receive spectral light waves can reflectthe spectral light waves. A waveform sensor can detect these light wavesand the control circuit can receive 5733 an input corresponding to thewaves reflected thereby.

Still referring to FIG. 27 , the control circuit can then assess theproximity of the needle and the tissue structure. For example, thecontrol circuit can determine, or calculate, 5734 a distance between theneedle and the tissue structure based on the received input. In at leastone instance, the data may include information to detect and determine aplurality of distances between multiple objects. For example, thecontrol circuit may determine a distance between the needle tip and thetissue structure, the trailing end of the needle and the needlestructure, and/or a plurality of sections of the needle and the tissuestructure. The control circuit is then configured to interpret 5735 thedata corresponding to the location of the objects detected. In at leastone instance, the distance(s) determined by the control circuit may becompared to a lookup table of predetermined, or predefined, safe, orcritical, distances. In at least one instance, the zoning methoddiscussed above may be used to compare the determined distances to.

Interpreting the data may also include the control circuit takingaction. For example, the control circuit can alert a clinician of thedetermined distance(s). The control circuit may alert a clinician onlyif the distance is less than or equal to a predefined critical distance.In at least one instance, the control circuit may alert the clinician ofthe distance via an audible indication, a tactile indication, and/or avisual indication, for example. In at least one instance, the controlcircuit may adjust the control motions being applied to the grasperand/or the waveform sensor by the clinician and/or the robotic system.In such an instance, for example, the control circuit may preventfurther actuation and/or, pause the actuation, of the grasper until anadjustment of the suturing location is made by the clinician and/orautomatically made by the robotic system at which point the algorithmcan be executed again if desired. Adjusting the control motions maycomprise applying reversing control motions to the grasper such that theneedle is reversed through its suturing stroke to back away from acritical structure. In at least one instance, the needle is reverseduntil it is a predefined safe distance away from the critical structureand the control circuit awaits further instruction from a clinician. Inat least one instance, the suturing stroke of the needle is completelyreversed so that the suturing needle is completely out of the tissuebeing sutured until the control circuit receives further instruction.All such adjustments can be made aware to the clinician during theprocedure. A clinician may also choose what type of adjust they wouldlike to occur open reaching the critical distance between the needle anda critical structure.

FIG. 28 is a flowchart depicting an algorithm, or process, 5740configured to be executed by a control circuit of a surgical suturingsystem. The process 5740 includes an automated suturing stroke such asthe one discussed above. In this process, the automated suturing strokeis initiated 5741 by a clinician using any suitable input. As discussedabove, the input may comprise an input may be delivered to the controlcircuit directly by a signal generated from a physical button that aclinician actuates or the input may comprise an automatically sensedcondition during the surgical procedure. For example, a camera maydetect a primed position of the needle and the grasper and use thatdetected image to begin the automated suturing stroke. Another exampleincludes sensing contact between a tip of the needle and tissue. Yetanother example may include beginning the suturing stroke manually afterthe system detects that the needle tip is in contact with the tissue andsuch initial manual movement triggers the automated suturing stroke bythe robotic system.

The process 5740 further employs a spectral light emitter to emit 5742spectral light waves into the surgical site and a waveform sensor todetect the location of the needle and/or embedded tissue structure. Thewaveform sensor collects data to be received 5743 as an input by thecontrol circuit with which the control circuit then uses to assess 5744the proximity of the needle and the tissue structure. As discussedabove, various types of calculations can be made by the control circuitbased on the data captured by the waveform sensor. Once the data isinterpreted by the control circuit and the proximity of the needle andthe tissue structure is assed, the assed proximity is then analyzed 5745to decide if the assed proximity is outside of a predefined criticalproximity range. For example, if the shortest distance detected betweenany part of the needle and any part of the tissue structure is 5 mm andthe predefined critical proximity range less than 10 mm, then thecontrol circuit will take appropriate action. In this example, if theshortest distance detected between the needle and the tissue structureis 15 mm, action may not be taken. In at least one instance, theclinician is made aware by the control circuit of the shortest distancebetween these structures at all times regardless of its relationshipwith a predefined critical proximity range. At any rate, if the assedproximity is within the predefined critical proximity range, the controlcircuit can take action 5746 such as any of those actions discussedabove. For example, pausing robotic actuation of the grasper, alerting aclinician of the condition, and/or automatically applying reversingcontrol motions to the grasper to move the needle away from the tissuestructure a desired distance may all include actions that could be takenby the control circuit.

At this point, the suturing stroke may not be complete. The state of thesuturing stroke is checked 5747 to determine if the suturing stroke mustcontinue. In at least one instance, the suturing stroke mayautomatically adjust 5746 the control motions applied to the grasper byreversing the suturing stroke completely so that the needle iscompletely out of the tissue. In such an instance, the clinician maythen be prompted to pick a new location for the suturing stroke and/or arobotic system may help or automatically pick a new location for thesuturing stroke. In another instance, the robotic system may applycontrol motions to the grasper to automatically navigate around thetissue structure. In another instance, the clinician may choose tooverride any adjustment suggested and may continue on with the automaticsuturing stroke and/or may continue the suturing stroke manually. Thereader should appreciate that “manually” can refer to manually operatinga robotic arm of a surgical robot to which the grasper and/or any othertool is connected with a robotic tool operating interface. The readershould also appreciate the “automatic” and/or “automated” can refer toactions, motions, and/or decisions being wholly or partially executed bya control circuit. Such a control circuit may comprise the logicdescribed herein. In another instance, information is fed to a controlcircuit of the robotic system to automatically move the robotic arm.

After a control motion adjustment, for example, is made, and it isdetermined that the suturing stroke is not complete, the suturing strokeis then continued 5748. At this point, the control circuit can monitorthese conditions in real time for example. In another instance, asdiscussed in greater detail below, this logic is performed prior to evenbeginning a suturing stroke and certain adjustments can be preempted bypredicting the path of the suturing stroke prior to puncturing tissuewith the needle.

FIG. 29 is a flowchart depicting an algorithm, or process, 5750configured to be executed by a control circuit of a surgical suturingsystem. The process 5750 includes an automated suturing stroke such asthe one discussed above. The process 5750 is similar to that of theprocess 5740 in some respects. However, the process 5750 includespredicting the path of the suturing stroke prior to beginning thesuturing stroke and/or puncturing the tissue with the needle. This canbe accomplished in different ways.

In at least one instance, the path of the suturing stroke is predictedby utilizing data known by the robotic system. For example, the positionof the robotic arm and, as a result, the grasper and the needle, can beknown within the robotic system itself. In at least one instance, datagenerated based on the position of the robotic controls with which aclinician operates the robot is communicated to the robotic system toposition the robotic arms accordingly. This data can be utilized in thesystems disclosed herein. In at least one instance, this data can bereceived by a control circuit and, along with known information aboutthe surgical needle such as arc length and overall size, the controlcircuit can determine and/or calculate the predicted path of thesuturing stroke given any position of the robotic arm.

In at least one instance, the path of the suturing stroke is predictedby using a waveform sensor and a spectral light emitter. In such aninstance, knowing the position of the robotic arm may not be necessary.The waveform sensor and spectral light emitter can detect the needledirectly and determine its position and shape. The control circuit canthen determine, based on the needle's current position and a knownsuture swing motion provided by the grasper, where in the tissue thesuturing stroke and, thus, the needle will pass. This results indetermining the predicted path of the needle at any given positionwithin the surgical site. In at least one instance, positional datacorresponding to components in the robotic system, predetermined datasuch as size of needle, and imaging data can all be used to determinethe predicted path of a suturing stroke.

Still referring to FIG. 29 , the process 5750 further includes detecting5753 any embedded tissue structures and assessing 5754 the proximity ofthe predicted path of the suturing stroke and the detected tissuestructures. In at least one instance, the shortest distance between thedetected tissue structures and the entire predicted path of the suturingstroke is conveyed to a clinician and/or within the surgical suturingsystem. In at least one instance, a range of distances defining aproximity field, or range, are conveyed to a clinician and/or within thesurgical suturing system. At any rate, assessing the proximity of thepredicted path of the suturing stroke and the needle can provide a wayto help ensure that each suturing stroke is performed outside of apredefined critical proximity range without puncturing tissue and havingto make an adjustment mid stroke. The predefined critical proximityrange can be selectable by a clinician and/or predefined based onsuturing standards.

If the predicted suturing stroke is entirely outside of the predefinedcritical proximity range, the robotic system may automatically perform5758 the suturing stroke with the grasper. In at least one instance, theclinician can initiate the automated suturing stroke after beinginformed by the control circuit that the predicted path of the suturingstroke is entirely outside of the predefined critical proximity range.If the predicted suturing stroke is within the predefined criticalproximity range, a variety of actions, adjustments, and/or alerts 5756may occur. In at least one instance, the clinician can be alerted thatthe predicted path falls within the critical range and can be promptedto select a manual override option where the robotic system canautomatically perform the suturing stroke and/or the clinician canmanually operate the robotic system to perform the suturing stroke. Inanother instance, the robotic system may automatically adjust thestarting position of the suturing stroke to recommend a new locationsuch that, at the new location, the new predicted path of the suturingstroke is entirely outside of the predefined critical proximity range.In at least one instance, the clinician is provided with several safeoptions regarding a new starting position for the suturing stroke andthe clinician can pick which option they would like to perform thesuturing stroke. In such an instance, the clinician can pick anotheroption and the robotic system can automatically move the robotic armand, thus, the grasper and the needle, to the new suggested location.The robotic system can then automate and perform the new suturingstroke. Nonetheless, the control circuit checks 5757 to see if thesuturing stroke is complete and continues to monitor the predicted pathof the suturing stroke based on the current position of the needle.

Referring now to FIG. 30 , a process 5760 configured to be executed by aclinician and/or a control circuit utilizing a robotically assistedsuture motion is illustrated. The process 5760 comprises an automaticshut off if a needle is within a defined proximity of a non visibleand/or embedded, critical structure. The process 5760 is initiated whena clinician operates a robotic arm to contact 5761 the surface of tissueto be sutured. If the clinician is satisfied with the placed position,the clinician can initiate 5762 the automatic suturing motion. In atleast one instance, a physical button is pressed by the clinician toinitiate the automatic suturing motion. The grasper then rotates 5763the needle through the tissue controlled by a robotic arm. At thispoint, or before this point at any time, the clinician may optionallyselect 5764 a critical distance at which the clinician wants to bemaintained between the needle and the critical structure. Such adistance may already be selected within the control program based onsensed conditions within the surgical site. In at least one instance,the distance is predefined and is based on suturing standards.

Still referring to FIG. 30 , the system visualizes 5766 any embeddedstructures and the needle, using an imaging system during the automaticsuturing stroke, and checks 5765 if the needle and the criticalstructure reach and/or surpass the critical distance. In at least oneinstance, the system looks for a critical distance that is less than thecritical distance. In at least one instance, the system looks for acritical distance that is less than or equal to the critical distance.In at least one instance, the system looks for a critical distance thatis approaching the critical distance and initiates an alert cycle beforethe critical distance is reached. Any suitable parameter other than orin addition to distance may be used. Also, the piercing tip of theneedle may specifically be visualized and checked using this process5760. Any suitable portion of the needle can be detected and used tomeasure the proximity between the needle and the tissue structure(s).

If the distance reaches the critical distance, the automatic suturingmotion is stopped 5767 and the clinician, or surgeon, is alerted of theproximity of the needle and the tissue structure. If the distance is notless than or equal to the critical distance, the automatic suturingmotion continues 5768 until the automatic suturing motion is completedby the robotic arm and, thus, the grasper. The system can monitor theproximity of the needle and any embedded tissue structures against theset critical distance during the entire automatic suturing motion. In atleast one instance, the proximity of the needle and any embedded tissuestructures are monitored during only a portion of the automatic suturingstroke. In at least one instance, the proximity of the needle and anyembedded tissue structures is monitored as long as the imaging systemcan detect one and/or both the needle and any embedded tissue structureswith the surgical site. At any rate, after the automated suturing motionis complete, the clinician grabs 5769 the piercing tip of the needle andpulls the needle and suturing material through the tissue to completethe suturing cycle. The clinician and/or the robotic system can thenreposition the needle to prepare for an additional stitch if desired atwhich point the process 5760 can be executed again.

Referring now to FIG. 31 , a process 5770 configured to be executed by aclinician and/or a control circuit utilizing a robotically assistedsuture motion is illustrated. The process 5770 is similar to the process5760 in many respects. The process 5770 comprises an automatic shut offif a needle is within a defined proximity of a non visible and/orembedded, critical structure. However, the process 5770 includes theability to predict the needle path in addition to monitoring theproximity of the needle and any embedded tissue structures in real time.In at least one instance, the either proximity monitoring method can beused exclusively. In at least one instance, a clinician can choose whichmethod they want to use to monitor the proximity of the needle and anyembedded tissue structures. In such an instance, the clinician maychoose both methods (suturing path prediction and real-time analysis).

The process 5770 is initiated when a clinician operates a robotic arm tocontact 5771 the surface of tissue to be sutured. If the clinician issatisfied with the placed position, the clinician can initiate 5772 theautomatic suturing motion. In at least one instance, a physical buttonis pressed by the clinician to initiate the automatic suturing motion.At this point, the algorithm determines 5773 if the proximity of theneedle and/or any part of the needle and any embedded tissue structuresvisualized by an imaging system is within a critical proximity rangebased on the current position of the needle. The system can determinethis by calculating the arc of the suture swing performed by the roboticarm and comparing that predicted path to the imaged position of theembedded structure(s). In at least one instance, the algorithm performsthis function automatically without a clinician needing to initiate itsuch that the information is already determined before the clinicianinitiates the automated suturing motion. At any rate, the automatedsuturing motion is not actuated if the proximity between the predictedpath and any embedded tissue structures is within a critical proximityrange. Such a range can be selectable and/or predefined.

If the predicted path is outside of the critical proximity range, thegrasper then rotates 5774 the needle through the tissue controlled by arobotic arm. At this point, or before this point at any time, theclinician may optionally select 5775 a critical proximity range at whichthe clinician wants to be maintained between the needle and/or thepredict path of the needle and the critical structure. Such a distancemay already be selected within the control program based on sensedconditions within the surgical site. In at least one instance, thedistance is predefined and is based on suturing standards.

Still referring to FIG. 31 , the system visualizes 5777 any embeddedstructures and the needle, using an imaging system during the automaticsuturing stroke, and checks 5776 if the needle and the criticalstructure reach and/or surpass the critical proximity range. If theproximity reaches the critical proximity range, the suturing motion isstopped 5778 and the clinician is alerted at which point a variety ofactions 5781 may occur. Such actions may include: the automatic suturingmotion is stopped, the needle is automatically retreated out of thetissue, the clinician is given manual control of the robotic system,and/or the robotic system determines a new path that would provide asuturing stroke outside of the critical proximity range and the roboticsystem navigates around the tissue structure. If the proximity is notwithin the critical proximity range, the suturing stroke is continued5779 until the suturing stroke is complete or until the criticalproximity range is reached. At any rate, once the suturing stroke iscomplete, a clinician and/or the robotic system can grab 5782 the needleto begin another stitch cycle if desired. In at least one instance, therobotic system can use data collected by the imaging system and/or thedata corresponding to the position of the robotics arm holding thegrasper and needle to determine the location of the needle tip so thatthe robotic system can automatically grab the tip of the needle one asuturing stroke is complete.

In at least one instance, an imaging system can be used to monitor theproximity between a suturing needle and a critical structure bydetecting variations in the tissue structure itself. For example, as theneedle displaces tissue during the suturing stroke or as the needle ispressed against tissue, this may result in pressure being applied to avein, for example. This pressure can cause a fluctuation in density ofthe vein. This fluctuation in density can cause the vein to reflectspectral light waves differently. For example, a vein unaffected by aneedle can comprise a lower density than a vein being pressed againstdirectly or indirectly by a needle in close proximity. Such densityfluctuation can provide different reflection signatures of the spectrallight waves. As a result, a hyperspectral camera can detect theproximity of the needle and the tissue structure, such as a vein, forexample, by only monitoring the spectral light reflection signatures ofthe vein. In another instance, the tissue around the vein can bemonitored in a similar fashion. In yet another instance, the surface ofthe vein or the barrier between the vein and the tissue can be monitoredfor variation in porosity as the needle affects the area. This may alsocause different spectral light reflection signatures. In at least oneinstance, a clinician can be alerted of the pressure being applied tothe tissue and/or tissue structures during a surgical suturingprocedure.

In at least one instance, a visualization system can be used to monitorthe flow of liquid through a vessel. For example, Doppler ultrasound maybe used to monitor the flow of blood, for example, through a vessel.During a suturing procedure, a needle may affect the flow of bloodthrough a vessel. For example, in at least one instance, flow of bloodmay slow due to a constricting condition created by the needle aroundthe vessel. In another instance, flow of blood may increase due to apuncture in the vessel itself. At any rate, the imaging system mayinclude Doppler ultrasound to detect rate of flow of liquid within avessel itself and, along with hyperspectral imaging, for example, canhelp prevent puncturing a blood vessel during a suturing stroke of aneedle. This information can be communicated to a control circuit andthus to a clinician during a surgical suturing procedure.

In at least one embodiment, a process utilizing a robotically-assistedsuturing motion is provided that comprises a shut off if a suture needleis in proximity of a non-visible critical tissue structure, according toat least one aspect of the present disclosure. The process prevents thesuture needle from contacting a tissue structure during robotic surgery.The clinician initiates the suturing process by touching a point on thesurface of the tissue. The clinician then selects the “penetrate” buttonto cause the suture needle, controlled by a robotically actuated,wristed grasper, to rotate through tissue. A warning distance between apath of the suture needle and the hidden tissue structure is set by theclinician to be a distance of X, such as 5 mm for example, and a tip ofthe suture needle is visualized by a hyperspectral imaging andvisualization system. The system checks to determine if the path of thesuture needle is within 5 mm of the tissue structure. If ‘yes’, thesystem stops rotation of the suture needle and indicates a proximitywarning to the clinician and if ‘no’, the system continues to rotate thesuture needle until the tip of the needle reaches a predetermined end ofrotation. The clinician then grabs the tip of the suture needle andrepositions it for the next stitch desired.

In at least one embodiment, hyperspectral imaging can visualize ametallic needle when buried by tissue. By having critical structuresidentified by this system in addition to the needle, a robotic systemcan help prevent the needle and a tissue structure from contacting eachother. In various instances, the suturing methodology described hereinis consistent with the “touch and turn” method of clinical instructionfor how to suture, generally. The clinician controls the “touch,” whichsets up needle and, specifically, needle tip placement and suturespacing (i.e. manipulate tissue to be sutured such that the stitchcaptures a desired width of tissue). The robotic system controls the“turn” (the suturing stroke—including the needle piercing and travelingthrough tissue) and has the ability to turn off the “turn” sequence if acritical structure is present. Any suitable technology may be used forsensing the needle, for example, within a surgical site. For example,sensing using ultrasound, magnetic sensing, and/or capacitive sensingmay be used to monitor the location of the needle.

In at least one embodiment, a process for suturing is provided utilizinga robotically-assisted suture motion and proximity suture motionprevention, according to at least one aspect of the present disclosure.The process prevents the suture needle from contacting a criticalstructure during robotic surgery. In this process, after the surgeonselects the “penetrate” button, based on the calculated arc of thesuture swing and known position of a hidden critical structure, thesystem prevents the rotation of the suture needle if the suture would bewithin a defined distance of the hidden critical structure. Thisdistance may be selectable by a clinician and/or predetermined.Furthermore, once the rotation is stopped, the system proceeds accordingto three options: (1) stop, retract, and/or back out suture; (2) givesurgeon control; and/or (3) auto navigate to avoid the hidden criticalstructure.

Examples

Various aspects of the subject matter described herein are set out inthe following numbered examples.

Example 1—A surgical suturing tracking system configured for use with asuturing needle. The surgical suturing tracking system comprises aspectral light emitter, a waveform sensor, and a control circuit coupledto the waveform sensor, wherein the control circuit is configured tocause the spectral light emitter to emit spectral light waves toward asuturing needle and a tissue structure, receive an input correspondingto the spectral light waves reflected by the needle and the tissuestructure, and determine a distance between the needle and the tissuestructure based on the received input.

Example 2—The surgical suturing tracking system of Example 1, whereinthe control circuit is further configured to alert a clinician of thedetermined distance between the needle and the tissue structure.

Example 3—The surgical suturing tracking system of Examples 1 or 2,wherein the control circuit is further configured to alert a clinicianof the determined distance between the needle and the tissue structurewhen the determined distance is less than or equal to a predefineddistance.

Example 4—The surgical suturing tracking system of Examples 1, 2, or 3,wherein the control circuit is further configured to compare thedetermined distance between the needle and the tissue structure to apredefined distance profile comprising a first zone indicative of adistance that is approaching a critical distance and a second zoneindicative of a distance that has reached the critical distance, andwherein the control circuit is further configured to alert a clinicianif the determined distance reaches at least one of the first zone andthe second zone.

Example 5—The surgical suturing tracking system of Examples 1, 2, 3, or4, wherein the control circuit is further configured to calculate arecommended suture bite depth.

Example 6—The surgical suturing tracking system of Examples 1, 2, 3, 4,or 5, wherein the control circuit is further configured to calculate arecommended suture bite width.

Example 7—The surgical suturing tracking system of Examples 1, 2, 3, 4,5, or 6, wherein the control circuit is configured to determine adistance between a tip of suturing needle and the tissue structure.

Example 8—A surgical suturing system comprising a robotically-assistedsuturing device. The robotically-assisted suturing device comprises agrasper configured to be manipulated automatically by a surgical robotand manually by a clinician and a suturing needle configured to beactuated through a suturing stroke by the grasper when automatic controlmotions are robotically applied to the grasper. The surgical suturingsystem further comprises a spectral light emitter, a waveform sensor,and a control circuit coupled to the waveform sensor and therobotically-assisted suturing device. The control circuit is configuredto cause the spectral light emitter to emit spectral light waves towardthe suturing needle and a tissue structure, receive an inputcorresponding spectral light waves reflected by the needle and thetissue structure, determine a distance between the needle and the tissuestructure, and adjust the control motions robotically applied to thegrasper when the determined distance between the needle and the tissuestructure is less than or equal to a predefined distance.

Example 9—The surgical suturing system of Example 8, wherein adjustingthe control motions comprises pausing actuation of the grasper.

Example 10—The surgical suturing system of Examples 8 or 9, whereinadjusting the control motions comprises applying reversing controlmotions to the grasper to reverse the suturing stroke of the needle.

Example 11—The surgical suturing system of Examples 8, 9, or 10, whereinthe control circuit is further configured to alert a clinician of thedetermined distance between the needle and the tissue structure.

Example 12—The surgical suturing system of Examples 8, 9, 10, or 11,wherein the control circuit is further configured to alert a clinicianof the determined distance between the needle and the tissue structurewhen the determined distance reaches the predefined distance.

Example 13—The surgical suturing system of Examples 8, 9, 10, 11, or 12,wherein the control circuit is further configured to calculate arecommend suture bite depth.

Example 14—The surgical suturing system of Examples 8, 9, 10, 11, 12, or13, wherein the control circuit is further configured to calculate arecommend suture bite width.

Example 15—The surgical suturing system of Examples 8, 9, 10, 11, 12,13, or 14, wherein the control circuit is configured to determine adistance between a tip of suturing needle and the tissue structure.

Example 16—A surgical suturing system comprising a robotically-assistedsuturing device. The robotically-assisted suturing device comprises agrasper configured to be manipulated automatically by a surgical robotand manually by a clinician and a suturing needle configured to beactuated through a suturing stroke by the grasper when automatic controlmotions are robotically applied to the grasper. The surgical suturingsystem further comprises a spectral light emitter, a waveform sensor,and a control circuit coupled to the waveform sensor and therobotically-assisted suturing device. The control circuit is configuredto cause the spectral light emitter to emit spectral light waves towarda suturing needle and a tissue structure, receive an input correspondingto the spectral light waves reflected by the needle and the tissuestructure, determine a position of the needle and a position of thetissue structure based on the received input, predict a path of thesuturing stroke to be performed by the robotically assisted suturingdevice based on the received input, and determine a distance between thepredicted path of the suturing stroke and the tissue structure.

Example 17—The surgical suturing system of Example 16, wherein thecontrol circuit is further configured to alert a clinician of thedetermined distance between the predicted path of the suturing strokeand the tissue structure.

Example 18—The surgical suturing system of Examples 16 or 17, whereinthe control circuit is further configured to alert a clinician of thedetermined distance between the predicted path of the suturing strokeand the tissue structure when the determined distance is less than orequal to a predefined distance.

Example 19—The surgical suturing system of Examples 16, 17, or 18,wherein the control circuit is further configured to compare thedetermined distance between the predicted path of the suturing strokeand the tissue structure to a predefined distance profile comprising afirst zone indicative of a distance that is approaching a criticaldistance and a second zone indicative of a distance that is equal to orless than the critical distance, and wherein the control circuit isfurther configured to alert a clinician if the determined distance iswithin at least one of the first zone and the second zone.

Example 20—The surgical suturing system of Examples 16, 17, 18, or 19,wherein the control circuit is configured to determine a distancebetween a predicted suturing stroke path of a tip of the suturing needleand the tissue structure.

Example 21—A surgical suturing system comprising a grasper configured tobe manipulated automatically by a surgical robot and manually by aclinician, a suturing needle configured to be actuated through asuturing stroke by the grasper, and a control circuit. The controlcircuit is configured to receive an input from the clinician to causethe surgical robot to actuate the needle through the suturing strokeautomatically, determine a distance between the needle and a tissuestructure, compare the distance to a predefined critical distance, andadjust control motions applied to the grasper by the surgical robot ifthe determined distance is less than or equal to the predefined criticaldistance.

Example 22—The surgical suturing system of Example 21, wherein thepredefined critical distance is selectable by the clinician.

Example 23—The surgical suturing system of Examples 21 or 22, furthercomprising a spectral light emitter and a waveform sensor configured todetect spectral light reflections to detect the position of the needleand the position of the tissue structure.

Example 24—The surgical suturing system of Examples 21, 22, or 23,wherein adjusting control motions applied to the grasper comprisesapplying reversing control motions to reverse the suturing stroke.

Example 25—The surgical suturing system of Examples 21, 22, 23, or 24,wherein adjusting control motions applied to the grasper comprisespausing the application of control motions to the grasper to pause thesuturing stroke.

Example 26—The surgical suturing system of Examples 21, 22, 23, 24, or25, wherein adjusting control motions applied to the grasper furthercomprises giving manual control of the grasper the clinician.

Example 27—The surgical suturing system of Examples 21, 22, 23, 24, 25,or 26, wherein adjusting control motions applied to the graspercomprises automatically adjusting the control motions applied to thegrasper to navigate away from the tissue structure and continuing thesuturing stroke.

Example 28—The surgical suturing system of Examples 21, 22, 23, 24, 25,26, or 27, wherein the control circuit is further configured to alertthe clinician if the determined distance is less than or equal to thepredefined critical distance.

Example 29—The surgical suturing system of Examples 21, 22, 23, 24, 25,26, 27, or 28, wherein the determined distance comprises the distancebetween a tip of the needle and the tissue structure.

Example 30—The surgical suturing system of Examples 21, 22, 23, 24, 25,26, 27, 28, or 29, wherein the input corresponding to the position ofthe needle is generated by at least one of an ultrasonic device, amagnetic sensor, and a capacitive sensor.

Example 31—A surgical suturing system comprising a grasper configured tobe manipulated automatically by a surgical robot and manually by aclinician, a suturing needle configured to be actuated through asuturing stroke by the grasper, and a control circuit. The controlcircuit is configured to predict a path of the suturing stroke afterreceiving an input from the clinician, detect a tissue structure, andassess proximity of the predicted path and the detected tissuestructure.

Example 32—The surgical suturing system of Example 31, wherein assessingthe proximity of the predicted path and the detected tissue structurecomprises determining a shortest distance between the predicted path andthe detected tissue structure.

Example 33—The surgical suturing system of Examples 31 or 32, whereinthe control circuit is further configured to alert the clinician if theassed proximity is within a predefined critical proximity range.

Example 34—The surgical suturing system of Example 33, wherein thepredefined critical proximity range is selectable by the clinician.

Example 35—The surgical suturing system of Examples 31, 32, 33, or 34,further comprising a spectral light emitter and a waveform sensorconfigured to detect spectral light reflections to detect the tissuestructure.

Example 36—The surgical suturing system of Examples 31, 32, 33, 34, or35, wherein the control circuit is further configured to apply anautomatic control motion to the grasper to perform the suturing strokeif the assessed proximity is not within a predefined critical proximityrange.

Example 37—The surgical suturing system of Examples 31, 32, 33, 34, 35,or 36, wherein the control circuit is further configured to recommend adifferent location to begin the suturing stroke when the assessedproximity is within a predefined critical proximity range such that, atthe different location the suturing stroke would define a different pathoutside of the predefined critical proximity range.

Example 38—The surgical suturing system of Examples 31, 32, 33, 34, 35,36, or 37, wherein the control circuit is further configured to allocatemanual control to the clinician when the assessed proximity is within apredefined critical proximity range.

Example 39—The surgical suturing system of Examples 31, 32, 33, 34, 35,36, 37, or 38, wherein the control circuit is further configured toautomatically adjust control motions applied to the grasper to navigatethe predicted path away from the tissue structure outside of apredefined critical proximity range and continue the suturing stroke.

Example 40—The surgical suturing system of Examples 31, 32, 33, 34, 35,36, 37, 38, or 39, wherein the assed proximity comprises determining ashortest distance between a predicted path of a tip of the needle andthe tissue structure.

Example 41—A surgical suturing tracking system configured to detect andguide a suturing needle during a surgical suturing procedure, whereinthe surgical suturing track system comprises a control circuitconfigured to predict a path of a needle suturing stroke after receivingan input from a clinician, detect an embedded tissue structure, andassess proximity of the predicted path and the detected embedded tissuestructure.

While several forms have been illustrated and described, it is not theintention of Applicant to restrict or limit the scope of the appendedclaims to such detail. Numerous modifications, variations, changes,substitutions, combinations, and equivalents to those forms may beimplemented and will occur to those skilled in the art without departingfrom the scope of the present disclosure. Moreover, the structure ofeach element associated with the described forms can be alternativelydescribed as a means for providing the function performed by theelement. Also, where materials are disclosed for certain components,other materials may be used. It is therefore to be understood that theforegoing description and the appended claims are intended to cover allsuch modifications, combinations, and variations as falling within thescope of the disclosed forms. The appended claims are intended to coverall such modifications, variations, changes, substitutions,modifications, and equivalents.

The foregoing detailed description has set forth various forms of thedevices and/or processes via the use of block diagrams, flowcharts,and/or examples. Insofar as such block diagrams, flowcharts, and/orexamples contain one or more functions and/or operations, it will beunderstood by those within the art that each function and/or operationwithin such block diagrams, flowcharts, and/or examples can beimplemented, individually and/or collectively, by a wide range ofhardware, software, firmware, or virtually any combination thereof.Those skilled in the art will recognize that some aspects of the formsdisclosed herein, in whole or in part, can be equivalently implementedin integrated circuits, as one or more computer programs running on oneor more computers (e.g., as one or more programs running on one or morecomputer systems), as one or more programs running on one or moreprocessors (e.g., as one or more programs running on one or moremicroprocessors), as firmware, or as virtually any combination thereof,and that designing the circuitry and/or writing the code for thesoftware and or firmware would be well within the skill of one of skillin the art in light of this disclosure. In addition, those skilled inthe art will appreciate that the mechanisms of the subject matterdescribed herein are capable of being distributed as one or more programproducts in a variety of forms, and that an illustrative form of thesubject matter described herein applies regardless of the particulartype of signal bearing medium used to actually carry out thedistribution.

Instructions used to program logic to perform various disclosed aspectscan be stored within a memory in the system, such as dynamic randomaccess memory (DRAM), cache, flash memory, or other storage.Furthermore, the instructions can be distributed via a network or by wayof other computer readable media. Thus a machine-readable medium mayinclude any mechanism for storing or transmitting information in a formreadable by a machine (e.g., a computer), but is not limited to, floppydiskettes, optical disks, compact disc, read-only memory (CD-ROMs), andmagneto-optical disks, read-only memory (ROMs), random access memory(RAM), erasable programmable read-only memory (EPROM), electricallyerasable programmable read-only memory (EEPROM), magnetic or opticalcards, flash memory, or a tangible, machine-readable storage used in thetransmission of information over the Internet via electrical, optical,acoustical or other forms of propagated signals (e.g., carrier waves,infrared signals, digital signals, etc.). Accordingly, thenon-transitory computer-readable medium includes any type of tangiblemachine-readable medium suitable for storing or transmitting electronicinstructions or information in a form readable by a machine (e.g., acomputer).

As used in any aspect herein, the term “control circuit” may refer to,for example, hardwired circuitry, programmable circuitry (e.g., acomputer processor including one or more individual instructionprocessing cores, processing unit, processor, microcontroller,microcontroller unit, controller, digital signal processor (DSP),programmable logic device (PLD), programmable logic array (PLA), orfield programmable gate array (FPGA)), state machine circuitry, firmwarethat stores instructions executed by programmable circuitry, and anycombination thereof. The control circuit may, collectively orindividually, be embodied as circuitry that forms part of a largersystem, for example, an integrated circuit (IC), an application-specificintegrated circuit (ASIC), a system on-chip (SoC), desktop computers,laptop computers, tablet computers, servers, smart phones, etc.Accordingly, as used herein “control circuit” includes, but is notlimited to, electrical circuitry having at least one discrete electricalcircuit, electrical circuitry having at least one integrated circuit,electrical circuitry having at least one application specific integratedcircuit, electrical circuitry forming a general purpose computing deviceconfigured by a computer program (e.g., a general purpose computerconfigured by a computer program which at least partially carries outprocesses and/or devices described herein, or a microprocessorconfigured by a computer program which at least partially carries outprocesses and/or devices described herein), electrical circuitry forminga memory device (e.g., forms of random access memory), and/or electricalcircuitry forming a communications device (e.g., a modem, communicationsswitch, or optical-electrical equipment). Those having skill in the artwill recognize that the subject matter described herein may beimplemented in an analog or digital fashion or some combination thereof.

As used in any aspect herein, the term “logic” may refer to an app,software, firmware and/or circuitry configured to perform any of theaforementioned operations. Software may be embodied as a softwarepackage, code, instructions, instruction sets and/or data recorded onnon-transitory computer readable storage medium. Firmware may beembodied as code, instructions or instruction sets and/or data that arehard-coded (e.g., nonvolatile) in memory devices.

As used in any aspect herein, the terms “component,” “system,” “module”and the like can refer to a computer-related entity, either hardware, acombination of hardware and software, software, or software inexecution.

As used in any aspect herein, an “algorithm” refers to a self-consistentsequence of steps leading to a desired result, where a “step” refers toa manipulation of physical quantities and/or logic states which may,though need not necessarily, take the form of electrical or magneticsignals capable of being stored, transferred, combined, compared, andotherwise manipulated. It is common usage to refer to these signals asbits, values, elements, symbols, characters, terms, numbers, or thelike. These and similar terms may be associated with the appropriatephysical quantities and are merely convenient labels applied to thesequantities and/or states.

A network may include a packet switched network. The communicationdevices may be capable of communicating with each other using a selectedpacket switched network communications protocol. One examplecommunications protocol may include an Ethernet communications protocolwhich may be capable permitting communication using a TransmissionControl Protocol/Internet Protocol (TCP/IP). The Ethernet protocol maycomply or be compatible with the Ethernet standard published by theInstitute of Electrical and Electronics Engineers (IEEE) titled “IEEE802.3 Standard”, published in December, 2008 and/or later versions ofthis standard. Alternatively or additionally, the communication devicesmay be capable of communicating with each other using an X.25communications protocol. The X.25 communications protocol may comply orbe compatible with a standard promulgated by the InternationalTelecommunication Union-Telecommunication Standardization Sector(ITU-T). Alternatively or additionally, the communication devices may becapable of communicating with each other using a frame relaycommunications protocol. The frame relay communications protocol maycomply or be compatible with a standard promulgated by ConsultativeCommittee for International Telegraph and Telephone (CCITT) and/or theAmerican National Standards Institute (ANSI). Alternatively oradditionally, the transceivers may be capable of communicating with eachother using an Asynchronous Transfer Mode (ATM) communications protocol.The ATM communications protocol may comply or be compatible with an ATMstandard published by the ATM Forum titled “ATM-MPLS NetworkInterworking 2.0” published August 2001, and/or later versions of thisstandard. Of course, different and/or after-developedconnection-oriented network communication protocols are equallycontemplated herein.

Unless specifically stated otherwise as apparent from the foregoingdisclosure, it is appreciated that, throughout the foregoing disclosure,discussions using terms such as “processing,” “computing,”“calculating,” “determining,” “displaying,” or the like, refer to theaction and processes of a computer system, or similar electroniccomputing device, that manipulates and transforms data represented asphysical (electronic) quantities within the computer system's registersand memories into other data similarly represented as physicalquantities within the computer system memories or registers or othersuch information storage, transmission or display devices.

One or more components may be referred to herein as “configured to,”“configurable to,” “operable/operative to,” “adapted/adaptable,” “ableto,” “conformable/conformed to,” etc. Those skilled in the art willrecognize that “configured to” can generally encompass active-statecomponents and/or inactive-state components and/or standby-statecomponents, unless context requires otherwise.

The terms “proximal” and “distal” are used herein with reference to aclinician manipulating the handle portion of the surgical instrument.The term “proximal” refers to the portion closest to the clinician andthe term “distal” refers to the portion located away from the clinician.It will be further appreciated that, for convenience and clarity,spatial terms such as “vertical”, “horizontal”, “up”, and “down” may beused herein with respect to the drawings. However, surgical instrumentsare used in many orientations and positions, and these terms are notintended to be limiting and/or absolute.

Those skilled in the art will recognize that, in general, terms usedherein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to claims containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should typically be interpreted to mean “atleast one” or “one or more”); the same holds true for the use ofdefinite articles used to introduce claim recitations.

1. A surgical suturing system, comprising: a grasper configured to bemanipulated automatically by a surgical robot and manually by aclinician; a suturing needle configured to be actuated through asuturing stroke by the grasper; and a control circuit configured to:receive an input from the clinician to cause the surgical robot toactuate the needle through the suturing stroke automatically; determinea distance between the needle and a tissue structure; compare thedistance to a predefined critical distance; and adjust control motionsapplied to the grasper by the surgical robot if the determined distanceis less than or equal to the predefined critical distance.
 2. Thesurgical suturing system of claim 1, wherein the predefined criticaldistance is selectable by the clinician.
 3. The surgical suturing systemof claim 1, further comprising a spectral light emitter and a waveformsensor configured to detect spectral light reflections to detect theposition of the needle and the position of the tissue structure.
 4. Thesurgical suturing system of claim 1, wherein adjusting control motionsapplied to the grasper comprises applying reversing control motions toreverse the suturing stroke.
 5. The surgical suturing system of claim 1,wherein adjusting control motions applied to the grasper comprisespausing the application of control motions to the grasper to pause thesuturing stroke.
 6. The surgical suturing system of claim 5, whereinadjusting control motions applied to the grasper further comprisesgiving manual control of the grasper the clinician.
 7. The surgicalsuturing system of claim 1, wherein adjusting control motions applied tothe grasper comprises automatically adjusting the control motionsapplied to the grasper to navigate away from the tissue structure andcontinuing the suturing stroke.
 8. The surgical suturing system of claim1, wherein the control circuit is further configured to alert theclinician if the determined distance is less than or equal to thepredefined critical distance.
 9. The surgical suturing system of claim1, wherein the determined distance comprises the distance between a tipof the needle and the tissue structure.
 10. The surgical suturing systemof claim 1, wherein the input corresponding to the position of theneedle is generated by at least one of an ultrasonic device, a magneticsensor, and a capacitive sensor. 11-21. (canceled)
 22. A surgicalsuturing system, comprising: a grasper selectively manipulatable by asurgical robot or a clinician; a suturing needle configured to beactuated through a suturing stroke by the grasper; and a control circuitconfigured to: receive an input from the clinician to cause the surgicalrobot to actuate the needle through the suturing stroke; determine adistance between the needle and a tissue structure; compare the distanceto a predefined critical distance; and adjust control motions applied tothe grasper by the surgical robot based on the comparison.
 23. Thesurgical suturing system of claim 22, wherein the predefined criticaldistance is selectable by the clinician.
 24. The surgical suturingsystem of claim 22, further comprising a spectral light emitter and awaveform sensor configured to detect spectral light reflections todetect the position of the needle and the position of the tissuestructure.
 25. The surgical suturing system of claim 22, whereinadjusting control motions applied to the grasper comprises applyingreversing control motions to reverse the suturing stroke.
 26. Thesurgical suturing system of claim 22, wherein adjusting control motionsapplied to the grasper comprises pausing the application of controlmotions to the grasper to pause the suturing stroke.
 27. The surgicalsuturing system of claim 26, wherein adjusting control motions appliedto the grasper further comprises giving manual control of the grasperthe clinician.
 28. The surgical suturing system of claim 22, whereinadjusting control motions applied to the grasper comprises automaticallyadjusting the control motions applied to the grasper to navigate awayfrom the tissue structure and continuing the suturing stroke.
 29. Thesurgical suturing system of claim 22, wherein the control circuit isfurther configured to alert the clinician if the determined distance isless than or equal to the predefined critical distance.
 30. The surgicalsuturing system of claim 22, wherein the determined distance comprisesthe distance between a tip of the needle and the tissue structure.
 31. Asurgical suturing system, comprising: a grasper selectivelymanipulatable by a surgical robot or a clinician; a suturing needleconfigured to be actuated through a suturing stroke by the grasper; anda control circuit configured to: receive an input from the clinician tocause the surgical robot to actuate the needle through the suturingstroke; determine a distance between the needle and a tissue structure;detect the determined distance reaching or surpassing a predefinedcritical distance; and adjust control motions applied to the grasper bythe surgical robot based on the detection of the distance reaching orsurpassing the predefined critical distance.